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5

Table of Content006 Better Banking . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Adrian Docherty & Franck ViortChapter 2: The Global Financial Crisis

037 Pricing and Hedging Financial Derivatives . . . . .Leonardo Marroni & Irene PerdomoChapter 1: An Introduction to the Major Asset Classes

055 Project Risk Management. . . . . . . . . . . . . . . . . . .Yuri Raydugin Chapter 1: Nature of Project Uncertainties

082 Operational Risk Management. . . . . . . . . . . . . . .Philippa X. GirlingChapter 1: Definition and Drivers of Operational Risk

097 The Road to Recovery . . . . . . . . . . . . . . . . . . . . . .Andrew SmithersChapter 2: Why the Recovery Has Been So Weak

108 Code Red . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .John Mauldin & Jonathan TepperChapter 1: The Great Experiment

129 Angela Merkel . . . . . . . . . . . . . . . . . . . . . . . . . . . .Alan Crawford and Tony CzuczkaChapter 2: Revelation (Five Minutes to Midnight)

145 The Warren Buffett Way, Third Edition . . . . . . . .Robert G. HagstromChapter 1: A Five Sigma Event

165 Bonds are Not Forever . . . . . . . . . . . . . . . . . . . . .Simon LackChapter 1: From High School to Wall Street

188 The Dao of Capital . . . . . . . . . . . . . . . . . . . . . . . . .Mark SpitznagelChapter 1: The Daoist Sage

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Better BankingUnderstanding and Addressing the Failures in Risk Management, Governance and RegulationAdrian Docherty & Franck Viort978-1-118-65130-8 • Hardback • 376 pages • January 2014

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7

The Global Financial Crisis

2

The current, ongoing fi nancial crisis has shaken the world economy and the global banking sector. Many publications, of differing quality and emphasis, are available for those who wish to study the factual history of the fi nancial crisis. Here, we consider the crisis more from a thematic rather than a narrative perspective: the goal is to derive insights into the causes of the crisis that might help us consider improvements in the banking industry, rather than simply recounting facts or telling a sensational story.

2.1 FROM DEREGULATION TO DOTCOM CRASH

The world economy and fi nancial system underwent a major change in the 30 or so years running up to the crisis. Politically, many nations embraced the free-market doctrines of Reagonomics and Thatcherism, which had appeared to triumph over various forms of socialism and centrally planned economies. Logistically, the world became smaller and more integrated through advances in communication and transport. Technologically, rapid increases in computing power enabled vastly enhanced data processing, storage and ana-lytics. These factors shaped developments in the structure and innovation of the banking system.

Arguably, the changes were most pronounced in Europe. Deregulation of banking in the UK (the “Big Bang” of 1986) opened up the industry to new fi rms from abroad and kick-started a resurgence in London’s importance as the pre-eminent global fi nancial cen-tre. At the European level, the Single European Act in 1986 reinforced the concepts of competition limiting barriers to goods and services. The foundations for the Common Currency to become the Euro laid during this period followed a similar objective of closer trade integration between members but also the creation of a reserve currency that would compete with the US Dollar and provide European borrowers with a vast and liquid capital market. And widespread privatisations in the 1980s and 1990s introduced the culture of share ownership to a European populace whose main fi nancial asset had previously been a traditional bank deposit.

New types of companies entered the banking market. A breed of investment fi rms emerged that became known as “hedge funds”. The archetypal hedge fund was largely unregulated and aimed to exploit market imperfections, by fi nding trading positions that were offsetting yet differently priced and so certain to make a profi t, no matter in which direction the fi nancial markets moved. Hedge funds fi nanced themselves with their founders’ and clients’ investment capital, together with short-term debt facilities from the banks with whom they traded. Since the hedge funds were active trading customers of the banks, the banks were keen to provide them with loans. The hedge funds employed highly intelligent quantitative analysts, who used the latest databases and computing power to build risk arbitrage models. Since the funds were hedging their positions, the number-crunchers’ models generally showed that the hedges were

c02.indd 7 10/4/13 11:01 AM

8

8 Better Banking

not perfect – but they were pretty good and only a very odd circumstance would cause prob-lems. The models also demonstrated that such an odd circumstance would only be expected to occur once in every 10,000 years or so. Hence, the hedge funds felt like a pretty safe bet and a good source of earnings for all involved, so long as the disaster of biblical proportions didn’t show up.

In 1998, a disaster of biblical proportions did show up. Or at least, something highly unu-sual occurred, which the models had not anticipated. The fi nancial markets were spooked by the unexpected default by Russia on its international bonds and this triggered a “fl ight to quality” reaction from international investors. Their sudden and massive shifts in investment preferences, for example moving their portfolios out of thinly-traded or illiquid bonds into safer and more liquid bonds, caused problems for a large hedge fund called “Long Term Capi-tal Management” (LTCM). LTCM had credibility: it counted the winners of the 1997 Nobel Prize in Economic Sciences among its partners. Guided by their strong belief in the power of risk modelling (Myron Scholes and Robert Merton had helped develop the Black-Scholes option pricing model), they had a different way of thinking about the fi nancial world and “by putting numerical odds on its likelihood of loss”,1 they were supposedly able to generate superior trading strategies, certain to win against all the less sophisticated investors. But its trading strategy failed and resulted in massive losses that threatened to destabilise the capital markets through contagion.

Had the failure of LTCM triggered the seizing up of markets, substantial damage could have been inflicted on many market participants, including some not directly involved with the firm, and could have potentially impaired the economies of many nations, including our own.2

The Federal Reserve orchestrated a bail-out by LTCM’s lenders, so that the hedge fund did not need to close its positions at “fi re sale” prices into fragile markets. A crisis was averted. In the end, LTCM lost “only” around $5bn and its lenders did not need to write off their loans. In retrospect, however, the LTCM episode should have served as a forewarning on the risks that were building up in the fi nancial system.

At the turn of the century, the “dotcom” bubble was a crisis that never happened. Investors chased technology and “new era” stocks higher and higher and were largely wiped out when most of the dotcom businesses failed to convert their concepts into profi ts and experienced share price crashes. The main benchmark of the dotcom era, the NASDAQ index, peaked above 5,000 in early 2000 having been around 2,000 two years earlier, and fell to just above 1,000 two years later.3 The value of the stock holdings of US households fell from $18,100bn in early 2000 to $9,900bn in the second half of 2002.4 Wall Street banks were indeed investigated by New York Attorney Eliot Spitzer, leading to prosecution and settlement, owing to practices that mismanaged the confl ict of interest between research departments and investment bank-

1 When Genius Failed: The Rise and Fall of Long-Term Capital Management, Roger Lowenstein, 2000.2 Private-sector refi nancing of the large hedge fund, Long-Term Capital Management, Alan Greenspan testimony before the Committee on Banking and Financial Services, US House of Representatives,1 October 1998.3 From WSJ.com.4 Some Refl ections on the Crisis and the Policy Response, Ben S. Bernanke, 13 April 2012.

c02.indd 8 10/4/13 11:01 AM

9

The Global Financial Crisis 9

ing salespeople. But there was no banking collapse to combine with the collapse of the high-tech sector. This has puzzled some analysts:

The dotcom crash was of a similar magnitude to the subprime crisis while its output effects were small in comparison.5

and

The fall of dot-com stock prices just a few years earlier, which destroyed as much or more paper wealth – more than $8 trillion – resulted in a relatively short and mild recession and no major fi nancial instability.6

Why did the dotcom crash not create a serious crisis? It is true that banks did need to write off some of the dud loans to high-tech companies. For example, WorldCom had debt of $41bn when it went bankrupt in 2002. But the losses on dotcom investments did not cause conta-gion and second-order problems, because they were, for the most part, not fi nanced by debt. Investors saw their wealth grow, soar, explode and crash, but they were not left with a debt “hangover”.

Bubbles in themselves aren’t always bad. But when they leave behind debts, they can be disas-trous.7

The specifi c problems and vulnerabilities that led to today’s crisis were not present during the dotcom crash. Nevertheless, the authorities were concerned at the economic slowdown that was induced by the end of the dotcom bubble and the terrorist attacks of 11 September 2001.

2.2 THE SEEDS OF A CRISIS

Had I been in love, I could not have been more wretchedly blind. But vanity, not love, has been my folly8

Greenspan’s Low Interest Rates The response of the authorities to the economic slowdown was to lower interest rates to spur economic activity. At the New York Federal Reserve (“the Fed”), Governor Alan Greenspan lowered interest rates and kept them low. By admitting that the Fed could “mitigate the fallout when it occurs and, hopefully, ease the transition to the next expansion”,9 Greenspan signalled there would be a safety net in case the market crashed, providing justifi cation for a more aggressive approach to risk and “implicitly encouraged bankers to borrow short-term while making long-term loans, confi dent the Fed would be there if funding dried up”.10

5 Bubbles, Banks, and Financial Stability, Kosuke Aokiy and Kalin Nikolovz, August 2011.6 Some Refl ections on the Crisis and the Policy Response, Ben S. Bernanke, 13 April 2012.7 Masters of Nothing, Matthew Hancock and Nadhim Zahami, 2011.8 Pride and Prejudice, Jane Austen, 1813.9 Economic Volatility, Alan Greenspan, 30 August 2002.10 Fault Lines, R. Rajan, 2010.

c02.indd 9 10/4/13 11:01 AM

10

10 Better Banking

American interest rates were below 2% throughout the three years 2002, 2003 and 2004. In retrospect, this overly accommodative monetary policy sowed the seeds of a boom that became the backdrop of the current fi nancial crisis. Holding rates so low for so long was “the original sin of the Bernanke-Greenspan Fed” that was bound to lead to excessive risk-taking.11

The other implication of the actions of the authorities, notably the Fed, was to give investors a clear indication that action would always be taken to avoid calamity. The capital markets interpreted this as an implicit backstop to risk, a guarantee that distressed markets would be revived by public policy. In market-speak, this was termed the “Greenspan put”. Implicitly, it increased the risk appetite of the markets and reduced investors’ attention to downside risk. If things went wrong, the Fed would sort it out.

A Growing Trade Imbalance, a Savings Glut and Financial InnovationDuring this same period, global trade continued to grow and new, structural imbalances emerged that changed the nature of the international fi nancial system.

The imbalance was caused by Western economies importing ever more goods from Asia. Western consumers were borrowing to fi nance their consumption and Western governments were borrowing to fi nance budget defi cits, while Asian consumers and governments were saving and investing. The global fi nancial system facilitated this imbalance and enabled the transfer of Asian savings to Western borrowers. A “savings glut” emerged, which kept market interest rates low despite the higher fi nancing needs of the West. Developing economies were “shifting from being net importers of fi nancial capital to being net exporters, in some cases very large net exporters”.12

This shift occurred at the turn of the century. According to offi cial statistics,13 the current account of industrialised countries had moved from a surplus in 1999 to an annual defi cit of 1.5% of world GDP in 2006. Emerging markets and oil-producing countries were the mirror image, as the graph in Figure 2.1 shows. Poorer countries were lending money to richer coun-tries to buy their exports.

11 Anna Schwartz blames Fed for sub-prime crisis, The Telegraph, 13 January 2008.12 The Global Saving Glut and the U.S. Current Account Defi cit, Ben S. Bernanke, 10 March 2005.13 World Economic Outlook, IMF, April 2007.

–2

–1.5

–1

–0.5

0

0.5

1

1.5

20052000199519901985198019751970

Industrial Countries

Emerging Market and Oil‐ProducingCountries

Figure 2.1 Current account surplus/defi cit in % of world GDP

c02.indd 10 10/4/13 11:01 AM

11


The aforementioned political changes culminated with the introduction of the Euro at the turn of the century, which created a new, deep and liquid capital market. For the fi rst time, European borrowers could borrow effi ciently from bond investors in their own currency, as American companies had been able to for decades.

Technological advances spurred fi nancial innovation. New techniques for transferring risk boosted the activity of the bond markets. The biggest innovations were securitisation, funding arbitrage vehicles and the “credit default swap” (CDS). These are described below; they grew rapidly in size and complexity, while offering a seemingly perfect way for risk to be spread to new investors and thus reduce the overall risk in the system.

To illustrate the rapid and exponential growth in new fi nancial products, consider the growth of the CDS market. A CDS is a contract where the seller gives protection against the default of the reference entity in exchange for a fee. It is like an insurance policy against default. Buyers of protection could use CDS to reduce their exposures for tactical or strategic reasons. Sellers of protection could use CDS to generate risk-based revenues, without the hassle of making loans. Traders could use CDS to take positions in the market where they felt there was value to be earned. The total of all credit default swap transactions grew from next-to-nothing in 2001 to $60,000bn in 2007 – see Figure 2.2.

Financial engineering took on the aura of alchemy and its complexity outstripped the sophistication of investors and regulators. All areas of the fi nancial industry – including its regulators, managements and even its customers – were fi lled with such confi dence that they began to ignore the fundamentals of risk.

The head of the Federal Deposit Insurance Corporation in the USA noted that there had arisen a “prevailing belief that fi nancial markets, through fi nancial engineering, had created a system where risks were easily identifi ed and transferred from parties who were risk averse to those who were willing, ready and capable to assume these risks. The collapse of these markets calls these beliefs into question.”14

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

200920082007200620052004200320022001

Figure 2.2 Growth in the Credit Default Swaps market ($bn)15

14 Managing the transition to a safer fi nancial system, Sheila C. Bair, Chairman, Federal Deposit Insur-ance Corporation, September 2009.15 ISDA.

c02.indd 11 10/4/13 11:01 AM

12

12 Better Banking

Just as technology has transformed the fi elds of communications and transport, making things possible that were unthinkable a couple of decades prior, so did people assume that fi nance could also leap forward and give them the ultimate “Holy Grail” of risk-free reward. In this pursuit, banks and investors were happy to trust the risk assessment of specialised third-party agencies, who had devised tools to identify and measure the risk in the capital markets. The credit ratings agencies gave ratings to securitisation bonds (see Section 3.8.3), which were made up of portfolios of mortgage loans or similar assets. By splitting up the portfolio into slices, different investors could take different risk profi les on the same pool of mortgages, some with higher risk and a higher return and others with less risk and a lower return. Investors – including some of the most sophisticated banks in the world – trusted the expertise of the ratings agencies and their assessment of the riskiness of the mortgage portfo-lio and how the individual slices spread that risk. In a nutshell, securitisation appeared to be the perfect tool to provide a high-yield, low-risk product for investors and low cost fi nance for borrowers. The securitisation market quadrupled in the run-up to the fi nancial crisis, as shown in Figure 2.3.

At the same time, there was the rise of a new type of funding arbitrage vehicle in the wholesale market: the “conduit” and the “Specialised Investment Vehicle” (SIV). Although the names make them sound complex, in fact they did something very straightforward. They invested in (supposedly) high quality, long-dated investments and borrowed at low rates on a short-term basis. The arbitrage created a profi t stream that seemed risk-free, for the risk of their funding sources evaporating was not seen as a worry. Again, clever technology appeared to offer a breakthrough and people loved it.

Faced with a wall of money seeking a decent yield in a low-interest rate environment, the new effi ciency of the capital markets led to an odd situation: money became too cheap. This is illustrated in a chart from early 2007, which featured in the Bank of England’s Financial Stability Report. The chart in Figure 2.4 breaks down the cost of borrowing into the cost a risk-free investment (the bottom layer), the risk of the borrower (middle two layers, both expected

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

0

2000

ABCP USCDO US

2001 2002

Growth of the securitization market in the US and Europe 2000-2009 ($bn)

2003

MBS USCDO Europe

2004

MBS EuropeCDO2 US

20062005

ABS USCDO2 Europe

2007 2008

ABS EuropeABCP Europe

End‐June 2009

Figure 2.3 Growth of the securitisation market in the US and Europe ($bn)16

16 Global Financial Stability Report, IMF, October 2009.

c02.indd 12 10/4/13 11:01 AM

13


and unexpected loss, see Section 3.3) and the “residual” cost (the top slice in the chart). This slice can be thought of as the return that the lender gets by putting their money to work. It collapses to zero towards the end of 2006. Banks and bond investors were simply not being compensated for the provision of funds. Clearly, the disciplines of caveat emptor and market-based pricing were not being observed.

The factors set out above are the consequences of deeper imbalances in the global economy, in which “the US fi nancial sector bridged the gap between an overconsuming and overstimu-lated United States and an underconsuming and understimulated rest of the world”.18

Note that, unlike many commentators, we do not single out the excessive leverage, lack of capital, scarcity of on-hand liquidity reserves or weak term funding structures as causes of the crisis. Why? Because we see these as second-order factors, symptoms of the underlying failure of risk management and over-confi dence. Whilst it is true that banks would have fared better during the crisis if they had had better fi nancial resources, it must be stressed that more capital, more liquidity and more funding are not themselves remedies for the weaknesses of the banking industry.

17 Financial Stability Report, Bank of England, April 2007, sourced from Bloomberg, Merrill Lynch, Thomson Datastream and Bank of England calculations.18 Fault Lines, R. Rajan, 2010.

Residual (including illiquidity)Uncertainty about default lossExpected default lossRisk-freeActual Per cent

16

14

12

10

8

6

4

2

2070605040302012000991998

0+

–

Figure 2.4 Decomposition of borrowing costs over time17

Note from the original source chart: Decomposition of borrowing costs for UK high-yield corporates. The decomposition assumes a debt maturity of 20 years. For details, see Churm, R and Panigirtzoglou, N (2005), ‘Decomposing credit spreads’, Bank of England Working Paper no. 253.

c02.indd 13 10/4/13 11:01 AM

14

14 Better Banking

2.3 “WHY DIDN’T ANYONE SEE THIS COMING?”

A much wider cast of characters share responsibility for the crisis: it includes domestic politicians, foreign governments, economists like me, people like you. Furthermore, what enveloped all of us was not some sort of collective hysteria or mania. Somewhat frighten-ingly, each one of us did what was sensible given the incentives we faced. Despite mount-ing evidence that things were going wrong, all of us clung to the hope that things would

work out fi ne, for our interest lay in that outcome. Collectively, however, our actions took the world’s economy to the brink of disaster, and they could do so again unless we recog-

nize what went wrong and take the steps needed to correct it.19

This question, asked by many including by Queen Elizabeth II at the London School of Economics in November 2008,20 has one very clear answer: they did. But no-one paid too much attention: the warnings were not acted upon. “The threats to global fi nancial stability that were bound to result from the build-up of severe macroeconomic fi nancial imbalances were noticed and widely commented upon, but did not lead to any concrete policy action

19 Fault Lines, R. Rajan, 2010.20 Daily Mail, 6 November 2008.

Table 2.1 <Caption to come>

Feature Impact

Politics and society Massive confi dence and belief in free marketsPoor oversight of the banking industry (by shareholders, management and supervisors)

Risk management failures and loose underwriting standardsGive property access to even the poorer, who did not benefi t from globalisation

Low interest rates Policy-induced boom in asset prices and borrowing

Recycling of trade balance surplus in Asia into Treasuries keeping rates low

Global imbalances Asian savings lead to savings “glut” and a Western borrowing binge

Widening of trade surplus in some countries

Introduction of the Euro More liquidity, cheaper and greater levels of fi nance available

Abundant liquidity No attention to liquidity risk: money is infi nite and elastic

“Greenspan put” Increased risk appetite due to limited downside

Financial innovation More ways to manage risk but also easier ways for investors to misprice risk

Combination of the above Decline of investor discipline and neglect of caveat emptor rule

Interconnectedness Huge growth in the number and value of transactions between fi nancial counterparties

AU: Please provide citation for Table 2.1.

c02.indd 14 10/4/13 11:01 AM

15


aimed at reducing these imbalances”.21 Perhaps the clearest indicators of tensions and risk were the excellent analyses in the April 2007 edition of the Bank of England’s “Financial Stability Report” (FSR). As well as the chart referenced earlier, showing that borrowing costs were too low, the FSR gives very clear and accessible analyses that were, in aggregate, wholly supportive of the view that fi rm action of some sort was required. These analyses charted, amongst other items, the continuing rise in share prices, the declining risk premium demanded by investors, the increasing delinquency in American subprime home loans, the increasing indebtedness of UK corporates, and the rapid growth in the size of major inter-national banks’ balance sheets. The FSR concludes its risk assessment, observing in classic British understatement that:

In practice, the vulnerabilities are unlikely to be exposed in isolation, since several are interde-pendent and a number could be triggered by common shocks. An increasingly likely stress sce-nario would be a sharp unwinding of low risk premia, which then triggered a pickup in corporate defaults as credit conditions tightened. The unwinding of leveraged positions in corporate credit markets could lower market liquidity, amplifying falls in asset prices. The sharp movements in some markets in late February and early March highlight the potential for a more marked adjust-ment in asset prices if underlying conditions were to change more fundamentally. If price falls led to a generalised retreat from risk-taking, and a rise in correlation across asset markets, the scope for diversifi cation against such shocks would be reduced. In such a scenario, the sustainability of high revenues generated by “originate and distribute” business models could be called into question.22

In retrospect, the analyses are highly relevant, if not completely prescient. The FSR assumed that corporate credit defaults would be the major feature of any unwind, rather than the bank-ing sector itself. But still, it is disappointing that such clear warnings from a leading authority had such little impact. At the time, several people observed that fi nancial bubbles were like parties and “it is essential to take away the punchbowl when the party gets going”.23 But they all acknowledged the diffi culty of such actions.

The fragility and risk of the monoline insurance industry was highlighted by Bill Ackmann at length well before the subprime collapse,24 while clear warnings during the early stages of the over-heating of house prices internationally were well documented by such authoritative institutions as the IMF.25

Later chapters deal with proposals meant to ensure that early warning signals are acted upon and that risk management remains at the fore, even when confi dence is at a peak.

Advocates of market-led regulation were disappointed by the fact that market indicators did not anticipate the scale of the risks that were building up in the banking industry. If we look at a diverse set of fi ve blue-chip banks in Table 2.2, we can see how unpredictive these market measures26 were:

21 Reform of the global fi nancial architecture: a new social contract between society and fi nance, Hugo Banziger, Chief Risk Offi cer, Deutsche Bank.22 Financial Stability Report, Bank of England, April 2007.23 Implementing the macroprudential approach to fi nancial regulation and supervision, Claudio Borio, Head of Research and Policy Analysis, Bank for International Settlements.24 Is MBIA Triple A?: A Detailed Analysis of SPVs, CDOs, and Accounting and Reserving Policies at MBIA, Inc., Gotham Partners Management Co., LLC, 9 December 2002.25 World Economic Outlook: The Global Demographic Transition, IMF, September 2004.26 Bloomberg.

c02.indd 15 10/4/13 11:01 AM

16

16 Better Banking

Table 2.2 Overview of rating, equity valuation and CDS levels of major banks between 2007 and 2013

August 2007 August 2009 February 2013

Barclays Bank

S&P Credit Rating AA stable AA− negative A+ negative

Stock Price-to-Book Value Multiple

2.11 0.94 0.68

Credit Default Swap (5yr senior) 35 84 138

UBS

S&P Credit Rating AA+ stable A+ stable A stable


2.50 1.51 1.29


Deutsche Bank

S&P Credit Rating AA stable A+ stable A+ negative


1.36 0.84 0.65


Handelsbanken

S&P Credit Rating AA− stable AA− stable AA− negative


1.79 1.45 1.56

Credit Default Swap (5yr senior) − 75 64

Morgan Stanley Bank

S&P Credit Rating AA− stable A+ negative A negative


1.76 1.07 0.74

Credit Default Swap (5yr senior) (USD)

82 140 139

The same information for banks that needed to be resolved in some manner or other makes for grim reading (Table 2.3).

On the eve of the onset of the fi nancial crisis, popular perception was that banks were a safe bet and the source of perpetual growth with little downside. Their profi ts were seen as real and not the product of an increasing level of risk. Typical of this sentiment was an article in mid-2006 in Fortune magazine entitled: “Why bank stocks are cash machines: With their high yields and low P/Es, they offer the potential for solid long-term gains with little risk.”27 Quite simply, the mood was optimistic – naively so.

27 Fortune Magazine, 19 May 2006.

c02.indd 16 10/4/13 11:01 AM

17


Table 2.3 <Caption to come>

August 2007

Northern Rock

S&P Credit Rating A+ negative

Stock Price-to-Book Value Multiple 1.46

Credit Default Swap (5yr senior) 93

Lehman Bros.

S&P Credit Rating AA− stable


Credit Default Swap (5yr senior) (USD) 95

AIG Financial Products

S&P Credit Rating AA stable

Stock Price-to-Book Value Multiple (AIG) 1.33

Credit Default Swap (5yr senior) (USD) 66

HBOS

S&P Credit Rating AA- stable


Credit Default Swap (5yr senior) (March 2008) 195

Hypo Real Estate

S&P Credit Rating A- watch positive

Stock Price-to-Book Value Multiple (31 Dec 2007) 1.20

Credit Default Swap (5yr senior) –

2.4 THE BEGINNINGS OF A CRISIS

Although the tensions started to unwind during 2006, the fi rst ominous sign of an impending crisis was the profi t warning from HSBC on 7 February 2007 (see Section 5.4). It was disturb-ing, to say the least, for such a major bank to be announcing such a marked deterioration in the performance of its American business. However, for most people, the start of the fi nancial crisis was marked by the announcement by BNP Paribas on 9 August 2007, that it was freez-ing valuations on some of the funds that it administered on behalf of clients:

The complete evaporation of liquidity in certain market segments of the US securitisation market has made it impossible to value certain assets fairly regardless of their quality or credit rating. The situation is such that it is no longer possible to value fairly the underlying US ABS assets in the three above-mentioned funds. We are therefore unable to calculate a reliable net asset value (“NAV”) for the funds. In order to protect the interests and ensure the equal treatment of our investors, during these ex-ceptional times, BNP Paribas Investment Partners has decided to temporarily suspend the calculation of the net asset value as well as subscriptions/redemptions, in strict compliance with regulations.28

28 BNP Paribas News & Press Room website, release dated 9 August 2007.

c02.indd 17 10/4/13 11:01 AM

18

18 Better Banking

The fi rst months of the crisis were dubbed a “subprime crisis” and the jargon word “subprime” is now well understood around the globe. Of course, it refers to the mortgages provided to people who were unable to put down a large deposit for a house and unable, by conventional metrics, to pay down the mortgage balance over time. In fact, they were only able to service the interest payments due to subsidised introductory rates and only keen to take on the debt in the fi rst place in the hope of profi ting from rising real estate prices. Many subprime loans were for properties other than the primary dwelling of the borrower: they were speculative. The word “subprime” originates in the USA and it was in the USA that the market for subprime mortgages fl ourished. Banks and mortgage bro-kers were able to originate mortgages, parcel them up into securitisation structures and sell them off into the capital markets. The ratings agencies ran their cursory analyses and assigned AAA ratings to the vast majority of the mortgage pools. As we have seen, the quest for yield had led to investor myopia – they were duped by the superlative ratings and mispriced the risk.

When house price increases cooled off, the rising levels of mortgage delinquency led to losses in the subprime world. Several small subprime specialists had gone bust in 2006, but it was the HSBC profi t warning that initiated a more intense market focus on subprime expo-sures. Day after day, fi nancial institutions around the world disclosed their exposure to sub-prime and their estimate of the losses they faced. Evidently, the problem was not confi ned to just the loans themselves. In addition to subprime loans which the banks had themselves extended, exposure to the problem could arise via:

• Pooled loans within securitisation bonds; for some banks, this included securitisations that they had been building up for selling on (so-called “warehouses” of loans);

• CDOs: investments that had bought bonds from different securitisation pools and wrapped them together to create a pool-of-pools;

• CDO-squareds (a kind of pool-of-pool-of-pools);• SIVs (Special Investment Vehicles), which some banks had established to invest in long-

term subprime-related assets via short-term funding: quite simply, they were used as a low-risk “carry trade” (see Glossary);

• Inventory held within trading operations;• And for all of these, exposures that had been guaranteed by buying default insurance from

a specialised fi nancial guarantor or insurance company – the “monolines”.

These new structures were not irrelevant. For example, SIVs may sound like an esoteric back-water of the banking industry, but in aggregate they were huge: total SIV assets were over $300bn. Examples of SIVs include those shown in Table 2.4.

And SIVs were specialised in holding bank paper and securitisation bonds (Table 2.5).No-one could readily understand where the losses – which were clearly going to be enor-

mous – would hit. The global nature of the fi nancial markets and the complexity of the loans, which had been pooled and sliced multiple times and in myriad ways, made the question impossible to answer with any degree of certainty.

Banks started to disclose more details on their exposure profi les. Analysts and the media became familiar with the technical jargon and the pockets of subprime where losses were likely to be the greatest: which towns and cities, which year (or “vintage”) of loan, which rat-ing. But the fact that the subprime bonds were hardly being bought and sold in any volume in 2007 led to a situation where it was diffi cult to give a meaningful value to subprime securities

c02.indd 18 10/4/13 11:01 AM

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29 Moody’s takes rating action on certain Structured Investment Vehicles following its latest review of the sector, November 2007.30 SIVs: An Oasis of Calm in the Subprime Maelstrom, Moody’s, July 2007.

Table 2.4 Examples of SIVs making up 42% of total SIV holdings29

Name of the vehicle SponsorIssued Securities as of November 2007

Carrera Capital Finance HSH Nordbank AG $401m

Harrier Finance West LB AG $10.3bn

Kestrel Funding West LB AG $2.9bn

Asscher Finance Ltd HSBC $473m

Beta Finance Corporation Citigroup $16bn

Centauri Corporation Citigroup $16.9bn

Cheyne Finance Cheyne Capital $5.9bn

Cullinan Finance Ltd HSBC Bank plc $2.2bn

Dorada Coporation Citigroup $8.5bn

Five Finance Corporation Citigroup $10.3bn

Hudson-Thames Capital MBIA $495m

Links Finance Corporation Bank of Montreal $19.1bn

Nightingale Finance Ltd AIG $301m

Premier Asset Collateralised Entity Société Générale $4.3bn

Sedna Finance Coporation Citigroup $10.7bn

Tango Finance Ltd Rabobank $7.8bn

Victoria Finance Ltd Ceres Capital Partners $987m

Whistlejacket Capital Standard Chartered $4.9bn

White Pine Corporation Ltd Standard Chartered $4.3bn

Zela Finance Corporation Citigroup $2.5bn

Table 2.5 Breakdown of SIVs assets30

Financial 42.6%

RMBS 23.2%

CDO 11.4%

CMBS 6.1%

Credit card 5.0%

Student Loan 4.4%

Auto loan 1.1%

ABS 2.2%

Other 3.3%

c02.indd 19 10/4/13 11:01 AM

20

20 Better Banking

with a face value of trillions of dollars. The uncertainty itself became a source of risk that spread rapidly into the market through two major channels:

• Firstly and most obviously, it raised fears about the creditworthiness of the most exposed banks who might be facing the most severe losses.

• Secondly and less apparently, it increased the need for banks to have high quality assets to satisfy collateral posting obligations, in the case of derivatives. Where the assets of banks had declined in value and quality, their derivatives counterparties required them not only to top up the amount of collateral but also to improve its quality: increasingly, subprime bonds were not acceptable as collateral for such arrangements.

2.5 THE CRISIS INTENSIFIES

The crisis intensifi ed because of increasing fears about solvency, a continuing ebb of confi -dence away from all market participants and the drying up of liquidity across most dimen-sions. Systemic crises will tend to have these features: they are brought about by the interplay of solvency, confi dence and liquidity.

Banks that enjoy high levels of solvency should be the ones that are able to meet their obligations and hence maintain stable operations – depositors and investors should have confi -dence in them and continue to trust them with their funds, ensuring liquidity and the availabil-ity of funds when and where they are needed. When markets are benign, confi dence is strong and liquidity is ample: even banks pursuing high-risk strategies have little trouble attracting funds. Of course, the fl ipside of this is also true. As soon as confi dence evaporates, for what-ever reason investors’ fears can become a self-fulfi lling prophecy, as funding dries up and the viability of the bank is placed in doubt.

The second half of 2007 witnessed a slow degradation of the confi dence in the banking sys-tem. It became clear not only that subprime mortgage bonds were showing signs of signifi cant deterioration but also that these bonds were held in major volume by banks. But which ones? Some capital markets banks had tens of billions of dollars worth of subprime bonds in various parts of their businesses and, unsurprisingly, confi dence in these institutions started to take a hit. But it was by no means clear which banks were ultimately at risk, for subprime bonds had been distributed worldwide and packaged, repackaged and traded. Investors fretted about where the problems lay and how the crisis might unfold.

Market fears were for the solvency of the banks in question, yet they manifested them-selves in a liquidity crunch, caused by the withdrawal of funding in the securitisation markets and term funding markets. Banks that were reliant upon securitisation markets (Northern Rock is an example, see Section 5.11) faced real challenges making payments to their customers as they fell due and were forced to sell some of their (not infi nite) liquid asset buffers. Banks that could not obtain term funding took short-term funding, but this made the term structure of their balance sheets ever more fragile and increased the stress on the daily task of fund-raising from the market to stay operational. Credit Default Swap (CDS) is a proxy often used to measure the changes in credit risk perception by the mar-ket: the average CDS of 14 major international banks increased from 50bp to 300bp at the peak of the crisis – see Figure 2.5.

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21


Famous names became victims. For example, Bear Stearns had built up massive subprime-related exposures in several areas of its business. It became increasingly clear to market par-ticipants that it would have diffi culties facing its obligations. In early 2008, Bear Stearns was bailed out via a rescue package involving JP Morgan, which bought the fi rm, and the New York Federal Reserve, which provided a $30bn loan to enable the fi rm to avoid meltdown and the catastrophe of contagious market turmoil. At around the same time, AIG also came under threat when the level of risk in its balance sheet started to become apparent and counterparties started to demand collateral to be posted against their exposures.

The subprime crisis was seen as a resolvable crisis that would have episodic not systemic ramifi cations. Indeed, in the middle of 2008, a mild sense of optimism prevailed. The fun-damental belief in the robustness of banks remained intact, based as it was on the faith that fi rstly, banks are low credit risk compared to corporates and secondly, banks have practically infi nite and elastic access to cheap liquidity through the fi nancial markets. This faith was tested to destruction by the default of Lehman in September 2008.

2.6 MELTDOWN: THE LEHMAN BANKRUPTCY

“Smart risk management is never putting yourself in a position where you can’t live to fi ght another day”, says Mr Fuld32

Lehman’s bankruptcy was a turning point in the fi nancial crisis for the whole banking indus-try, as it revealed the systemic impact of the bankruptcy of a large bank. Since Lehman, no other major bank has been allowed to go bankrupt.

31 BIS.32 Fuld of experience: By learning from past mistakes, Dick Fuld has brought Lehman Brothers back from the brink, The Economist, 24 April 2008.

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Figure 2.5 Bank CDS spreads (in bp)31

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22 Better Banking

The days and weeks that followed the collapse of Lehman were uncharted territory for most market participants. At times, there was a sense of panic, at other times it was one of despond-ency. For the fi rst time in a long time, people feared for the survival of the global economic system.

Is this an exaggeration? No. “The US fi nancial system is fi nding the tectonic plates under-neath its foundation are shifting like they have never shifted before. It’s a new fi nancial world on the verge of a complete reorganisation,” noted Peter Kenny from Knight Equity Markets,33 while Bill Gross, the highly respected Chief Investment Offi cer of PIMCO, compared the panic that was seizing dealers who were having to unwind their positions to an “imminent tsunami”.34 Around that time, Alan Greenspan, the former Chair of the US Federal Reserve, horrifi ed by the fragility of the fi nancial system and the risk of a systemic collapse observed: “There’s no question that this is in the process of outstripping anything I’ve seen and it still is not resolved and it still has a way to go.”35

As banks attempted to rein in their exposures to other banks, there was a freeze in the interbanking market. Banks were simply unwilling to lend to each other. For years, banks had lent to each other at a rate that was essentially the same as the central bank’s policy rate. In mid-September 2008, that arrangement broke down. The rate at which banks were prepared to lend to each other (represented by LIBOR) rose to as much as 350bp (3.5%) above the central bank’s policy rate (represented by the “Overnight Index Swap” or OIS). Such a spike showed the extent of distrust in the banking industry towards other banks, as demonstrated by the graph in Figure 2.6.

A huge drop in market liquidity threatened to lead to forced selling of assets to meet pay-ments and a subsequent downward spiral in the value of fi nancial assets, which would put the solvency of all banks at risk. International trade, which relies on an effi cient banking system, could have ground to a halt, with a major impact on global economic activity. The economic shock to the system could have been similar to events that unfolded in the Soviet Union when it collapsed. The shock to the world economy could have been of the order of 20% or so in a short timeframe – at those levels, social unrest is not out of the question.

Lehman’s demise was followed by multiple bank failures, raising the threat of systemic crisis and destroying confi dence even further:

• AIG had to be rescued by the Federal Reserve on 16 September 2008.• Merrill Lynch had to be rescued by Bank of America during the same weekend that Lehman

fi led for bankruptcy.• HBOS was purchased by Lloyds TSB on 18 September.• Washington Mutual was purchased by JP Morgan on 26 September.• In Belgium, Fortis was nationalised on 28 September, while the Franco-Belgian bank Dexia

had to be recapitalised on 30 September.• Bradford and Bingley was nationalised before being bought by Santander in the UK on

28 September.

33 Bloody Sunday: Wall Street Is Hit by Financial Tsunami, CNBC.com, 14 September 2008.34 The Guardian, 15 September 2008.35 Greenspan to Stephanopoulos: This is “By Far” the Worst Economic Crisis He’s Seen in His Career, ABC News, 14 September 2008.

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23


• Wachovia was bought by Wells Fargo on 3 October. • Kaupthing, Glitnir and Landsbanki in Iceland had to be nationalised at the beginning of

October 2008.

September and October 2008 were dark days in the banking industry and the world economy. Banks dominated the headlines of the TV news every night and few commentators were able to propose a fi x.

2.7 MASSIVE INTERVENTION INTERNATIONALLY

Sensing the nature and scale of the danger, governments across the world responded with measures to keep the banking system alive.

Liquidity SupportCountries like the UK, France, Germany and Ireland put in place state guarantees to restore confi dence in bank lending. Banks would issue under their own name but the investor would benefi t from an unconditional guarantee from the home State. “Government Guaranteed Bonds” (GGBs) soon became a new asset class, bringing liquidity back to banks’ funding profi les and restoring banks’ ability to transform risk and access liquidity – Figure 2.7.

Central banks also played a crucial role by performing the role of “lender of last resort” and offering repo facilities to refi nance illiquid assets in the balance sheet of banks. In the Eurozone, the ECB monetary operations, originally organised as a tender for a predefi ned amount of liquidity and for a limited period soon turned into an unlimited offer of liquidity at a fi xed rate and for a period extending up to one year. The Special Lending Scheme (SLS) in the UK allowed British banks to obtain funding. Coordination among central banks also allowed access to foreign currency funding, vital for the global dollar-denominated business of European banks.

36 BIS Annual Report 2009.

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Figure 2.6 LIBOR-OIS spread (in bp)36

c02.indd 23 10/4/13 11:01 AM

24

24 Better Banking

The level of liquidity pumped into the economy between 2008 and 2009 is unprecedented. The balance sheet of the US Federal Reserve doubled in size.38 ECB lending to banks also doubled, from €400bn on average before the crisis to more than €800bn (see Figure 2.8).

Solvency SupportAs well as keeping money fl owing, in many countries, governments put in place solvency sup-port mechanisms to ease the fear of meltdown. As losses materialised, many struggling banks

37 IMF, Dealogic.38 US Federal Reserve.39 Annual Report 2010, IMF.

Figure 2.7 Issuance volumes of bonds by banks (global, $bn)37

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Figure 2.8 ECB lending to Eurozone banks (€bn)39

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Greece Ireland Ireland OtherSpain Portugal

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c02.indd 24 10/4/13 11:01 AM

25


were recapitalised by the state – see Figure 2.9. The aggregate value of these recapitalisations amounted to hundreds of billions of dollars.

In some cases, the state was forced to “sanitise” troubled banks by taking problematic assets from them or underwriting the value of such assets at a low level. The lessons of prior crises (in Sweden, for example, in the early 1990s) led some governments to set up separate “bad banks” for the problematic assets. This underwriting provided a valuable backstop to market fears, restoring some degree of confi dence to the banks’ balance sheet – see Table 2.6.

As the Lehman episode illustrates, state support is often seen as a preferable solution to bankruptcy. Authorities are working on better alternatives to state support (see Section 4.6 on resolution regimes, for example), but such alternatives were not available at the outset of the current crisis. In 2007, banks did not have high levels of capital or liquidity reserves; there were no “living wills” or resolution plans.

These actions, the magnitude of the commitment and the high level of coordination around the world soon produced dramatic effects: the fi nancial system, though still fragile, recovered from its fears of meltdown. In the second half of 2009, confi dence slowly returned, aided by some signifi cant measures by the authorities to improve the strength and resilience of the banking industry. In particular, new “stress tests” and an industry-wide increase in capital level requirements amounted to a public declaration on the strength of banks.

The Stress TestsMarket fears about the strength of banks were based upon the fact that the accounting and regulatory numbers no longer meant anything: they did not quantify the ability to withstand a further deterioration in the economic situation. Everyone knew that the losses in the banks’ portfolios could be greater than their capital reserves, but it was not possible to assess this using the information available. To meet this need, regulators required banks to run their fi nancials through a scenario of deteriorating conditions and report on what their capital levels were likely to be.

40 BIS Annual Report 2009,

Figure 2.9 Bank losses and capital injections ($bn)40

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Q1 2009Q4 2008Q3 2008Q2 2008Q1 2008Q4 2007Q3 2007

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c02.indd 25 10/4/13 11:01 AM

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26 Better Banking

Table 2.6 “Bad Bank” and solvency backstop mechanisms (examples)

Country Mechanism Description

Ireland NAMA (National Asset Management Agency)

NAMA was set up in December 2009 to cleanse the Irish banks of problem loans to property developers. Technically a private sector company (to keep the fi nances off the state’s balance sheet), NAMA bought loans with a face value of €74bn from the Irish banks at an assessed “market value”. In practice, this meant a discount of 58% from the nominal value. The loss on sale caused a severe solvency defi cit at the Irish banks, but improved their clarity of purpose and removed uncertainties around their viability. NAMA is actively working on the resolution of problem loans and has generated in excess of €10bn since inception.41

Switzerland StabFund UBS was burdened with around $60bn worth of investments in subprime bonds and similar. At the end of 2008, the StabFund was set up so that UBS “caps future potential losses from these assets, secures their long-term funding, reduces its risk-weighted assets, and materially de-risks and reduces its balance sheet”. The assets were transferred at independently appraised market prices as of 30 September 2008.

The equity in the StabFund is at a level of around 10% and the rest of the fi nancing is a loan from the Swiss National Bank. UBS issued convertible bonds to the Swiss Federation in order to fi nance the equity contribution and maintains an option to buy back the equity at a preferential price, should the assets perform well.42 The value of this upside to UBS shareholders was $2.3bn at the end of 2012.43

United Kingdom

APS (Asset Protection Scheme)

In order to improve the viability of RBS, the UK government set up the APS to provide insurance on losses above a certain level on a varied portfolio of troubled loans. The insured portfolio had a nominal value of £282bn and RBS was left with the exposure to fi rst losses up to £60bn, with the APS providing 90% insurance cover for losses beyond that and RBS retaining the exposure for 10% of losses (to keep RBS focused on minimising losses). The scheme terminated in late 2012. In total, RBS paid about £2.5bn for the insurance cover and, since losses were well within the “fi rst loss” layer, the government did not have to pay out anything.44

41 NAMA website (www.nama.ie).42 UBS further materially de-risks balance sheet through transaction with Swiss National Bank, UBS website, 16 October 2008.43 UBS Fourth Quarter Report 2012.44 RBS exits UK Government’s Asset Protection Scheme, The Royal Bank of Scotland Group plc, 17 October 2012.

c02.indd 26 10/4/13 11:01 AM

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Country Mechanism Description

Netherlands Illiquid assets back-up facility

ING had amassed a portfolio of €28bn worth of US subprime mortgage bonds, the potential risk of which was causing problems for the group. “Market prices for these securities have become depressed as liquidity dried up, which had an impact on ING’s results and equity far in excess of reasonably expected credit losses.”45 It agreed an “Illiquid Assets Back-up Facility” with the Dutch State covering 80% of the exposure, in return for a fee. The assumed value of the bonds was a discount of 10% of the par value, which was quite generous, since the bonds were trading at discounts of around 35% at the time.46 ING remained the legal owner of 100% of the securities and exposed to 20% of any results on the portfolio.

Belgium Asset Protection Plan

KBC had invested €20bn in CDOs, most of which were guaranteed by the troubled monoline credit insurer MBIA. These positions were causing a lot of problems for KBC and they wanted to remove the uncertainty. The asset protection plan provided by the Belgian State was in three layers. The fi rst layer of loss (€3.2bn) was all for KBC; the second layer (€2bn) was also down to KBC but with the state agreeing to buy KBC shares to cover 90% of the value of the loss; the third layer (€14.8bn) comprised coverage of 90% of credit losses by the state.47

Spain SAREB “La Sociedad de Gestión de Activos procedentes de la Reestructuración Bancaria” (Sareb) was set up in late 2012 to purchase troubled real estate loans from several Spanish banks. Its assets are set to rise from the initial €45bn to as much as €90bn. In most respects, it is similar to the Irish NAMA, though the transfer value of assets is curiously being described as “the real economic value of the assets”, which presumably means at a premium to open market price levels. Despite this generosity, Sareb is promising 15% annual return on equity to its private sector investors.48

US TARP Following the collapse of Lehman Brothers, the US Treasury created the Troubled Asset Relief Programme (TARP) as an exit strategy for fi nancial institutions holding subprime assets. The fund is under the responsibility of the US Treasury and has a capacity of $700bn of which $415bn was utilised at the end of April 2013.49 Assets are purchased against warrants from the seller and can be sold by the TARP to create capacity for more purchases. TARP has also been used to recapitalise banks directly through the Capital Purchase Programme.

45 ING update on results and measures to reduce risk and costs, ING Group, 26 January 2009.46 NautaDutilh advises on innovative ING – Dutch State deal Illiquid assets back-up facility may lead the way, NautaDutilh, April 2009.47 Overview of capital-strengthening measures agreed with the Belgian State and the Flemish Region, KBC, 6 August 2009.48 Restructuring and Recapitalisation of the Banking Sector: the Asset Management Company (Sareb), FROB, 29 October 2012.49 TARP monthly report to US Congress, April 2013.

c02.indd 27 10/4/13 11:01 AM

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28 Better Banking

The Federal Reserve, alongside the other US regulators (the FDIC and the OCC) conducted a “Supervisory Capital Assessment Program” (SCAP) on 19 American banks and released the results on 7 May 2009. The positioning of the results was meant to boost confi dence in the banking sector:

These examinations were not tests of solvency; we knew already that all these institutions meet regulatory capital standards. Rather, the assessment program was a forward-looking, “what-if” exercise intended to help supervisors gauge the extent of the additional capital buffer necessary to keep these institutions strongly capitalized and lending, even if the economy performs worse than expected between now and the end of next year. The results released today should provide considerable comfort to investors and the public. The examiners found that nearly all the banks that were evaluated have enough Tier 1 capital.50

In fact, the SCAP found that the banks needed to increase their capital by $75bn in aggre-gate, including $34bn for Bank of America.51 A series of capital increases ensued, mostly from the US government’s TARP programme (described above).

A few weeks later, the EBA stress test of 2009 found that all was well with Europe’s banks. Under a scenario that was worse than expected, European banks would lose €400bn, yet still maintain strong capital ratios: “the aggregate Tier 1 ratio for the banks in the sample would remain above 8% and no bank would see its Tier 1 ratio falling under 6% as a result of the adverse scenario.”52 Such a result was of little use. The markets knew that banks were vulnerable and wanted to see those vulnerabilities addressed. A clean bill of health did not assuage fears about European banks. Future stress test exercises in Europe would become a little more demanding.

The comforting message of the stress tests conducted in 2009 was designed to calm markets. In the USA, this may have been met, with the aid of government capital injections. In Europe, the stress tests were seen as a joke. The market was expecting a better elucidation of the weak-nesses of the banks, not an excuse. Market observers reacted badly, pouring scorn and predict-ing a “Japanese-style future for Western banks, in which a thinly capitalised system staggers along, insisting on its rude health, while the state follows holding crutches an inch beneath its armpits. If that is the answer, then the stress tests were asking the wrong question.”53

Basel III ProposalA week before Christmas 2009, the Basel Committee unexpectedly released its response to the fi nancial crisis, the proposals that were to become known as Basel III.54 The markets warmed to the proposals, which were seen to require signifi cant capital-raising and improvements in funding and liquidity structures. Over the coming weeks and months, analysts studied and interpreted the proposed rules, identifying those banks who would need to raise fresh equity in order to comply with the new, stronger standards. The effi cacy of Basel III is discussed in Section 4.5, though of course a long-awaited set of proposals in the regulatory framework did nothing to avert the immediate crisis.

50 Statement regarding the Supervisory Capital Assessment Program, Statement by Chairman Ben S. Bernanke, Federal Reserve, 7 May 2009.51 The Supervisory Capital Assessment Program: Overview of Results, Federal Reserve, 7 May 2009.52 CEBS’S Press Release on the Results of the EU-Wide Stress Testing Exercise, EBA, 1 October 2009.53 Hospital pass, The Economist, 14 May 2009.54 Consultative proposals to strengthen the resilience of the banking sector announced by the Basel Com-mittee, 17 December 2009.

c02.indd 28 10/4/13 11:01 AM

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2.8 SOVEREIGN CRISES

The subprime crisis caused the solvency of banks to be called into question. Confi dence and liquidity dried up. The bankruptcy of a major international bank threw the entire banking system into disarray and panic. Government support measures brought much-needed stability and confi dence back to the system and averted a disastrous meltdown. However, the “post-Lehman” period also carried a hangover.

It brought an abrupt end to the fi nancial boom that some countries had been experiencing, as debt-fuelled investment and construction programmes slowed down. In most countries, house prices corrected sharply, falling well below their stratospheric peaks. Consumer and corporate confi dence evaporated, causing domestic consumption and investment to shrink as discretionary spend was curtailed. People in all walks of life adopted a new-found – and, occasionally, rather fashionable – sense of austerity.

In a word, there was a weakening in overall economic growth and the stretching of the fi nances of some governments that had been forced to bail out their domestic banking sector.

The attention of economists turned to the fi nancial viability of governments and the capital markets started to fear the creditworthiness of the most distressed, whose borrowing needs were increasing. In general terms, there were two types of problems. Governments were forced to borrow more primarily to bail out their banking industry. And the fi nancial crisis brought into the foreground the issues of public sector profl igacy, over-indebtedness and structural problems in the real economy. The fear of sovereign default – practically unheard of in developed econo-mies in modern times – intensifi ed. According to Eurostat, the overall impact of government support to the fi nancial sector in Europe represented 5.2% of the European GDP in 2012.55

The macro-economic statistics tell an ugly story. The current fi nancial crisis has wrecked the creditworthiness of many countries, pushing them massively into defi cit and forcing them to add vast amounts of debt to their existing government borrowings. More disturbingly, eco-nomic growth has been knocked off-trend, resulting in a huge output loss of around a quarter of annual GDP or more (see Table 2.7). On an individual level, for many, there has been a permanent loss of wealth, security and happiness.

The health of the economy is key for healthy banks and so is the health of the government, for banks and their governments are heavily intertwined.

Banks play a key role in the national economy and are regulated by a government agency. If banking gets into trouble, the country can suffer and the state’s fi nancial position can be signifi cantly weakened. On the other hand, banks pay income taxes and employ people: they are direct contributors to the economy and the public budget. In some countries, the fi nancial services industry is a major sector of the economy.

Banks are also major buyers of the sovereign debt of their home country, or at least they traditionally have been. The concept of lending to the government is an odd one and for most of the time, banks treat their “sovereign” entity as risk-free. After all, most governments have the ability to print money to repay their debts and the cost of sovereign borrowing is com-monly used in fi nance as proxy for the “risk-free” rate as opposed to market return in models such as the CAPM. The natural asset for a bank to invest its liquidity portfolio may appear to be a risk-free government bond: indeed, liquidity regulation gives incentives for banks to hold sovereign debt as a liquidity buffer.

55 Support for fi nancial institutions increases government defi cits in 2012, 2013, Eurostat.

c02.indd 29 10/4/13 11:01 AM

30

30 Better Banking

The formidable convergence of sovereign yields following the creation of the Euro has hidden some fundamentally different economic realities in Greece, Portugal, Spain, Italy on the one had and Germany on the other. As Figure 2.10 suggests, the widening which started in 2009 may have been interpreted as a sign of tension in the Eurozone, but looking at the situation in 1999, it appears more like a correction. The fi nancial crisis and slower growth that ensued have put pressure on sovereign credit and the notion of a “risk-free” rate defi nitely counts as another victim of this crisis.

There is, however, no reason for banks to invest specifi cally in their own home country, they simply need liquid assets in their operating currency. The Euro creates a specifi c situation, in that the individual sovereigns are – for the time being at least – not mutually guaranteed and there is a discernible difference between the credit risk of different countries. Banks in Greece chose to buy Greek government bonds rather than lower-yielding German government bonds because it appeared profi table to do so. Nor is there a need for them to buy long-term govern-ment bonds as liquidity assets rather than short-term bonds or even cash. Again, banks that choose to buy longer-term instruments are generally seeking to increase their profi tability and reduce the “drag” of holding low-yield assets in their liquidity portfolios.

Table 2.7 Selected macro-economic indicators

Country

S&P credit rating

(April 2013)2007 Budget

Defi cit562012 Budget

Defi cit572012 Debt-to-

GDP ratio58 (%)

3 year output loss (as %

trend GDP)59

Banking Assets to GDP % (2012)60

USA AA+ neg −2.9% −7.6% 107 31 90

UK AAA neg −2.7% −7.7% 89 25 463

France AA+ neg −2.7% −4.5% 90 23 420

Germany AAA −0.2% +0.1% 83 11 326

Italy BBB+ neg −1.5% −2.9% 126 32 257

Spain BBB− neg −1.9% −7.4% 91 39 339

Greece B− −3.9% −7.6% 170 na 220

Ireland BBB+ +0.2% −8.5% 118 106 839

Portugal BB −2.7% −6.1% 119 37 300

Switzerland AAA +1.3% +0.3% 47 0 469

Australia AAA +1.8% −0.8% 27 na 202

Canada AAA +1.6% −3.8% 88 na 336

Japan AA− neg −2.5% −9.1% 237 na 196

56 Comparing Public Spending and Priorities Across OECD Countries, Center for American Progress, October 2009.57 World Factbook 2012, CIA.58 World Economic Outlook Database 2013, IMF.59 IMF.60 Sources: EBF, RBA, FSB, SNB.

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31


At any rate, for the countries currently under an IMF programme, it was the banks in Ireland that caused major problems for the sovereign (needing capital injections equivalent to 41% of GDP62), while in Greece and Portugal, it was the other way round: public sector weakness led to signifi cant direct losses for the banks (€26bn for Greek banks during the recent sovereign debt restructurings63 and €4bn for Portuguese banks as a “sovereign capital buffer” under the EU Capital Exercise of 201164). Later on in this book, we consider ways to reduce the linkage between sovereign and banks by removing the costs of bank bail-outs from the government’s responsibility and removing the need for banks to invest in the debt of their sovereign at all.

Sovereign weakness in the Eurozone has led to speculation that certain countries will be forced to leave the currency union. Corporations and consumers have gradually transferred large amounts of their money across borders within the Eurozone. This deposit fl ight, which has yet to develop into a full-blown run, along with the collective interest in keeping the Eurozone together, has resulted in the European Commission and the heads of governments moving forward with the project of a full Banking Union, structured around a European guarantee mechanism of deposits and European regulation of banks. This strategy seems an appropriate response for Europe, as the existence of a single currency makes no sense with-out other ancillary unions. It is patently a “double or quits” approach to a troubled situation: more Europe is the only way to save the Euro. We note the strange logic of a currency caus-ing a political situation rather than supporting it: this seems odd to a dispassionate observer, if not to a European. The political solution of “more Europe” may not be appealing to all

61 BNP Paribas.62 Ireland’s report card, Department of Finance, October 2012.63 PSI costs domestic lenders dearly, ekathimerini.com, 20 April 2012.64 EU Capital Exercise – Final results, EBA, 8 December 2011.

Figure 2.10 Relative Eurozone yields 61

2.5

3

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5

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6

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7

7.5

Jan/04Jan/03Jan/02Jan/01Jan/00Jan/99 Jan/06Jan/05 Jan/09Jan/08Jan/07 Jan/10

% Relative Eurozone yield 1999-2009

Germany Greece Portugal

c02.indd 31 10/4/13 11:01 AM

32

32 Better Banking

members of the European Union. In any case, it may be too late to build a proper banking union, as macro events may overtake the initiative. The situation with Cyprus’ currency controls, for example, shows us that the principles of currency union are precarious and open to compromise.

2.9 AFTERSHOCKS AND SKELETONS IN THE CUPBOARD

There is an insightful saying, widely attributed to the American investor, Warren Buffett: “It’s only when the tide goes out that you learn who’s been swimming naked.” For the banking industry, this wisdom has meant that it has taken a violent fi nancial crisis to fl ush out scandals and behaviours that are shocking and disturbing in the extreme. Though they are not directly related to the fi nancial crisis, they are still symptoms of failures in risk management.

Recent examples include those shown in Table 2.8.

Table 2.8 Selected examples of recent scandals affecting banks reputation

The LIBOR scandal

Several leading wholesale banks were found to have manipulated their reporting of the industry-standard interest rate, used to defi ne the interest payable on millions of customer contracts. This was either to avoid owning up to the true cost of funding during the depths of the crisis (i.e. under-reporting) or to attempt to manipulate LIBOR to make trading gains (i.e. mis-reporting). The investigations have uncovered incriminatory call recordings and e-mail conversations and severe management lapses. Major fi nes have been issued and several prominent management teams (e.g. Barclays’ CEO and COO) have been replaced.

Derivatives losses at Monte dei Paschi da Siena

In February 2013, the oldest bank in the world, Monte dei Paschi di Siena, reported an unexpected loss of €730m65 in some structured transactions that it had undertaken to boost earnings. Reporting on the story, Bloomberg commented that it showed “how investment banks devised opaque products that years later are leaving companies and taxpayers with losses. From the Greek government to the Italian town of Cassino, borrowers have lost money on bets that were skewed in banks’ favor.”66

Misselling of derivative products to small businesses (UK)

The UK FSA is currently investigating instances where small businesses were provided with interest rate derivatives without the appropriate process being followed, resulting in a fi nancial loss to the customer. “FSA found that over 90% of the sales of Interest Rate Hedging Products (IRHPs) to ‘non-sophisticated’ customers did not comply with one or more of our regulatory requirements.”67 In some cases, small businesses were pressured into contracts such as inverse fl oaters, where the interest rate on the loan falls when policy rates rise and rises when policy rates fall: these customers were left with unaffordably high rates on their loans when policy interest rates plummeted in 2008.

65 Monte dei Paschi di Siena investor relations website, 7 February 2013.66 Deutsche Bank Derivative Helped Monte Paschi Mask Losses, Bloomberg, 17 January 2013.67 Interest Rate Hedging Products, Pilot Findings, FSA, January 2013.

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33


Misselling of Payment Protection Insurance (PPI) to retail customers (UK)

During the last decade or so, UK retail banks got into the habit of pressuring retail customers who were taking out a loan into simultaneously taking out an insurance policy to cover the loan repayments in case of the borrower getting sick, becoming unemployed and other reasons. For many borrowers, this was a bad product, expensive and ineffective. For the banks, it appeared immensely profi table, with a profi t margin of about 80–90% of the product cost: payouts on the policies were rare and low. Banks are now being forced to recompense customers and some £14bn68 in redress provisions have already been taken, half of which is accounted for by Lloyds Banking Group69

“Even as we have got used to the iniquity of the banks, the latest revelations still take the breath away. The scale of the payment protection insurance (PPI) misselling scandal is truly gigantic. […] The banks sold 20 million PPI policies by 2006, and between 2001–10 amassed colossal sales of £34bn, equivalent to a quarter of the entire UK GDP.”70

Losses at JP Morgan’s “Chief Investment Offi ce” unit

In early 2012, some derivatives trading positions in a specialised unit at JP Morgan went wrong and lost the bank $5.8bn. The “CIO” unit was positioned as a natural hedge to the core business of JP Morgan. But “fl awed trading strategies, lapses in oversight, defi ciencies in risk management”71 led to the exposures getting out of control. (See Section 5.8)

Trading fraud: Kweku Adoboli at UBS

In September 2011, UBS announced that it had lost $2.3bn as a result of unauthorised trading conducted by Kweku Adoboli, a London-based trader in UBS’ synthetic equities team in London. The authorities concluded that the “rogue trader” fraud was not stopped because of of failures by UBS to adequately supervise the business and poor risk management processes. (See Section 5.10)

Contravention of sanctions and money-laundering abuses

A set of serious compliance breaches has recently come to light involving major international banks in their US operations. These breaches have related to failures to follow the correct procedures for dealing with customers, intended to reduce the risk of money-laundering and breaking of American sanctions against certain countries (e.g. Iran, Libya, Burma, Sudan). The banks involved were HSBC (see Section 5.4) and Standard Chartered.

FSA mystery shopping exercise

Again in the UK, the FSA has recently published the disappointing results of its “mystery shopper” exercise. “The FSA found that only three-quarters of customers received good advice and had concerns with the quality of advice in the other quarter.”72 Clearly, an industry where one-quarter of clients are receiving bad advice is worrying.

Evidently, there have been many scandals, damaging both fi nancially and reputationally. The ones above are mere highlights. It may be coincidence that these transgressions are com-ing to light at the present moment. But, more likely, it is that the banking industry suffered

68 Price bar lowered for Lloyds resale, Financial Times, 1 March 2013.69 Annual Report and Accounts 2012, Lloyds Banking Group.70 LIBOR isn’t half of it, Michael Meacher MP for Oldham West and Royton, 29 October 2012.71 Report of JP Morgan Chase & Co. Management Task Force Regarding 2012 CIO Losses, 16 January 2013.72 Assessing the quality of investment advice in the retail banking sector: A mystery shopping review, FSA, February 2013.

c02.indd 33 10/4/13 11:01 AM

34

34 Better Banking

severe and systemic lapses of risk management during the bubble years preceding the current fi nancial crisis. The environment will have contributed to bad behaviour, since undoubtedly “fi ddles are more remunerative and easier to conceal during an asset bubble”.73 There are almost certainly many more shocking episodes to unfold as the industry continues to fi nd “skeletons in the cupboard”. Hopefully, these revelations and episodes have highlighted cru-cial areas for improvement and positive change will result.

2.10 WHO IS TO BLAME?

The chief punishment is this: that no guilty man is acquitted in his own judgement.74

The current fi nancial crisis has had a major negative impact on the wealth and wellbeing of the global economy. Millions of people have had their lives transformed and tens of millions more have had their personal fi nancial situation damaged. Quantifi ed impact estimates relay the hard economic facts: in the European Union, for example:

Public intervention cost taxpayers substantial sums of money and even put some Member States’ public fi nances at risk. Between October 2008 and October 2011, the Commission approved€4.5 trillion (equivalent to 37% of EU GDP) in state aid measures to fi nancial institutions, of which €1.6 trillion (equivalent to 13% of EU GDP) was used in 2008–2010. Guarantees and liquidity measures account for €1.2 trillion, or roughly 9.8% of EU GDP. The remainder went towards recapitalisation and impaired assets measures amounting to €409 billion (3.3% of EU GDP). Budgetary commitments and expenditure on this scale are not sustainable from a fi scal point of view, and impose a heavy burden on present and future generations. Moreover, the crisis, which started in the fi nancial sector, pushed the EU economy into a severe recession, with the EU’s GDP contracting by 4.2%, or €0.7 trillion, in 2009.75

Beyond the data, the impact is quite clear: the experience of a fi nancial crisis is unpleasant, unfair and unacceptable.

Blame the BankersIt would be convenient to fi nd a single cause for the crisis, fi nd the appropriate remedies and thus resolve the problem. The popular media has tended to follow this approach and has fostered the view that there are specifi c parties to blame and that it is through their actions exclusively that the fi nancial crisis was brought about. Naturally, since this is a fi nancial crisis more than anything, there has been a desire to blame the banking industry – and bankers in particular – for the problems.

The specifi c aspect of banking that seems to draw popular ire is the asymmetry of gains and losses. This has been expressed several times as either “heads I win, tails you lose” or, to put it in more technical terms, “the privatisation of gains and the socialisation of losses”. This perceived asymmetry of risk and reward is not a new aspect of banking: in

73 An eternal chancer critiques RBS failures, Jonathan Guthrie, FT Lombard, 6 February 2013.74 Satires, Juvenal, c 100 AD.75 Staff Working Document 167, European Commission, 6 June 2012.

c02.indd 34 10/4/13 11:01 AM

35


1837, the President of the United States reportedly expressed his anger at such a situation: “Gentlemen, I have had men watching you for a long time and I am convinced that you have used the funds of the bank to speculate in the breadstuffs of the country. When you won, you divided the profi ts amongst you, and when you lost, you charged it to the bank. You tell me that if I take the deposits from the bank and annul its charter, I shall ruin ten thousand families. That may be true, gentlemen, but that is your sin! Should I let you go on, you will ruin fi fty thousand families, and that would be my sin! You are a den of vipers and thieves.”76

The perception of intense unfairness is reinforced when people see how much bankers are paid, in good times and in bad. Mega-bonuses are paid to senior bankers who are sup-posed to be superstars, yet are often exposed as unethical and incompetent. Bankers are highly paid and have not been seen to suffer unduly as a result of the crisis. They continue to collect bonuses, hardly any previous bonuses have been “clawed back” and scandals based on egregious behaviours continue to emerge. The banking industry seems rotten: “From excessive levels of compensation, to shoddy treatment of customers, to a deceitful manipulation of one of the most important interest rates, and now this morning to news of yet another misselling scandal, we can see that we need a real change in the culture of the industry.”77

Deeper Structural IssuesHowever, it would be wrong to assume that bankers’ culture alone brought about a fi nancial crisis of this proportion. This crisis may have reached its boiling point in the boardrooms and trading fl oors of banks around the world, but it has its roots in other, fundamental aspects of our economic and fi nancial system:

• Major, structural imbalances in our global economy, savings patterns and trade fl ows;• Excessive belief by all parties in the stability and sustainability of a loosely regulated, free-

market system;• Political inability to nip an asset bubble in the bud and rein in borrowing; indeed, the pro-

motion of popular yet unsustainable policies based on increasing levels of governmental and personal indebtedness;

• Major failings in risk management at banks, including an over-reliance on statistical tech-niques and insuffi cient challenge of assumptions; in a word, over-confi dence;

• Regulatory and supervisory failings on the part of several of the world’s leading fi nancial authorities;

• A crisis of governance in many of the world’s leading banks, with unclear accountability for ruinous strategies and management processes;

• Ineffective shareholder governance and accountability of regulatory and supervisory au-thorities (or to put it dramatically, a crisis of capitalism and democracy).

Limiting the analysis of this crisis to the behavioural issues of bankers may satisfy a psycho-logical need for retribution and give the public at large the confi rmation that they are innocent bystanders, but this will miss the point. Our ability to prevent further crises happening in the

76 Attributed to Andrew Jackson, President of the United States.77 Financial Stability Report Press Conference Transcript, Bank of England, 29 June 2012.

c02.indd 35 10/4/13 11:01 AM

36

36 Better Banking

future will depend on our ability to understand clearly what brought us to the predicament, in which we fi nd ourselves. Hating bankers may have become a global sport, but it does not solve the structural issues in our economy and banking system: “The wide appeal of scapegoating banking is motivated by a sense of incomprehension towards the workings of the world. In contrast to previous times, there is a relative dearth of accounts that provide a convincing structural explanation for the global economic upheaval. In such circumstances the wider structural imbalances that have affl icted the different spheres of economic life are diffi cult to discern. That is one reason why the fantasy that Wall Street and greedy bankers have brought down an otherwise robust economy is so widely upheld.”78

78 Hating bankers a global sport, The Australian, 8 February 2012.

c02.indd 36 10/4/13 11:01 AM

Pricing and Hedging Financial DerivativesA Guide for PractitionersLeonardo Marroni & Irene Perdomo978-1-119-95371-5 • Hardback • 264 pages • November 2013

Buy Now!


£60.00 £36.00 / €72.00 €43.20 / $100.00 $60.00


38

JWBK593-c01 JWBK593-Marroni Printer: Yet to Come September 26, 2013 13:34 Trim: 244mm × 170mm

1

An Introduction to the MajorAsset Classes

This introductory, and slightly eclectic, chapter focuses on the liquid investment asset classes inwhich derivatives and structured products are normally developed, priced and traded, namelyequities, fixed income, commodities and foreign exchange. The aim is not to describe in detailthe everyday products traded in these markets but more to give a sense of the general pricecharacteristics of these markets, e.g., how they move through time. There are many excellentproduct books on the market and we would recommend readers interested in the range ofproducts available to pick up a copy of one of them; we have listed some in the References.In this chapter, we aim to make some observations on how to model underlying asset price

behaviour for each asset class.1 In order to have a real understanding of the value that can beextracted from financial derivatives, one must understand how prices behave in their compositeparts. This is not a quantitative finance textbook, however, and we do not aim to be completelyrigorous. Instead, in this chapter as in the others, we try to get across an intuitive (rather thanan academic) understanding.2

On the way, we will also highlight some interesting features of the markets under review sothat you, the reader, can feel more personal affinity with them; we think that, if your interestis tweaked, you will enjoy the book (and the chapter) much more. Many readers of this bookwill have experience in one or two of these asset classes but probably not all. If short on time,you could, of course, read the sections on the least familiar asset classes and skip the rest. Thatsaid, if you do have some experience but you are a little rusty, the following sections shouldbe a good review.

1.1 EQUITIES

1.1.1 Introduction

Equities are perhaps the most familiar of the main asset classes. The shareholder capital orcapital stock (or, merely, stock) of a company represents the capital paid into or invested inthe business by its shareholders. Along with other assets in the firm, shareholder capital servesas security for the creditors of that company. The capital stock is divided into shares (alsocalled equity). The company may have different types (classes) of equity, each class havingdistinctive ownership rules, privileges and/or prices.Equity typically takes the form of common or preferred. Common shares typically carry

voting rights, which shareholders can exercise at certain times to influence the company and itsdirectors. Preferred shares typically do not carry voting rights but holders are legally entitledto receive their dividends before other shareholders. Since holders of preferred shares getpreferential treatment, they are called preference shares in the UK.

1 There will be a little mathematics but not much. Instead, we hope to explain the issues more intuitively.2 If you are looking for a quantitative finance textbook then probably anything by Wilmott is worthwhile.

COPYRIG

HTED M

ATERIAL

39


2 Pricing and Hedging Financial Derivatives

Convertible preferred shares are preferred shares that include an option for the holderto convert them into a fixed number of common shares, usually any time after apredetermined date.Preferred shares may sometimes have a hybrid structure, having the qualities of bonds (such

as a fixed percentage dividend) and common stock voting rights.

1.1.2 Pricing equities

The price of a single stock/share/equity (the terms are interchangeable) is determined as alwaysby the interaction of supply and demand. Factors that impact only on the single stock price arecalled stock-specific. These factors can include a change in CEO, new patents awarded to thecompany, new product development, etc. The prices of individual stocks are also influencedby factors that affect the entire equity market, however. These are market-specific. In fact,statistical analysis suggests that the majority of the variation in the prices of individual stocksusually comes about from events that impact the overall equity market, for example changes inmonetary policy or the risk tolerance of investors, rather than stock-specific factors. Stocks thattend to move by more than the overall market moves are called high-beta stocks while thosethat move less than the market are called low-beta stocks. This is essentially a carry-over fromthe Capital Asset Pricing Model (CAPM),3 which you do not really need to know much aboutfor the purposes of this book. High-beta stocks tend to be in cyclical sectors, such as consumerdurables, property and capital equipment. Low-beta stocks tend to be non-cyclical, such asfood retailers and public utilities. Another way of describing low-beta stocks is defensive.To be sure, there is a huge industry dedicated to predicting likely future movements in the

price of a single stock or equity market. The three main approaches are fundamental analysis,technical analysis and quantitative analysis. We discuss these techniques below. There aresome more esoteric theories of equity price determination, such as those predicated on sunspot activity or the Chinese horoscope, for example. What all these theories have in common,however, is that they have their fans as well as their detractors.Of course, investors could just ignore forecasting entirely and invest passively, judging that

the future direction of price movements is unpredictable in all but the long run. We will saymore on this below.

1.1.3 Fundamental analysis

Fundamental analysis attempts to use economics and accountancy to value a single stock orthe overall equity market (or sector), thereby obtaining the fair value price. Investors can thencompare the actual price with the fair value price and then decide whether the stock price orindex level is over- or undervalued. Put simply, analysts attempt to assess the likely flow ofcash flows from the company or the market as a whole and discount these using a relevantdiscount rate. The net present value of the future cash flows is then the equilibrium (or fairvalue) price of the equity or the overall market.

3 The beta is usually estimated by regressing the historic returns to the stock against the returns to the market over a given sampleperiod (for example, or one business cycle). Alternatively, beta may be interpreted as a stock’s contribution to the volatility of the totalmarket portfolio. In this case, it is the covariance of returns between the stock and the “market portfolio”, divided by the varianceof returns to the market portfolio. Variance is a measure of dispersion and is the square of the standard deviation of returns. One ofthe problems with stock betas, however, is that they are notoriously unstable and significantly different estimates will be obtaineddepending on the sample period selected for the price return histories.

40


An Introduction to the Major Asset Classes 3

Although discredited bymany, the EfficientMarkets Hypothesis (EMH) suggests that equitymarkets are essentially rational. That is, the price of any stock (and, consequently,market index)at any given moment represents a complete evaluation of the known information that mighthave a bearing on the future value of that stock. In other words, stock prices are, at any pointin time, equal to the sum of the discounted future cash flows. Furthermore, prices can onlychange if there is some “news” that has an effect on those future cash flows.4 In a sense, theEMH supports the idea of fundamental analysis although there is a chicken-and-egg problemhere. The EMH says that fundamental analysis to value a stock or equity market is unnecessarysince current stock prices are already at their fair value. But, of course, how did the marketarrive at the prices in the first place? Presumably some entity somewhere must be crankingout the numbers?In recent years, even the most die-hard fans of the EMH have come to accept that the

markets are not perfectly efficient, especially the least liquid ones. To quote Professor RobertSchiller, “the Efficient Markets Hypothesis is a half-truth”.

1.1.4 Technical analysis

Technical analysis attempts to predict future price changes in a single stock or the overallequity market (or sector) by analysing past price movements. Technical analysis is extremelypopular among certain market participants although there is considerable controversy attachedto its use. Certainly, if you subscribe to the school of thought that says that equity markets areefficient, then there is no place for technical analysis. For a more in-depth discussion of thispoint, see Chapters 10 and 11 of Financial Theory and Corporate Policy (2003) by Copeland,Weston and Shastri.Whichever approach you prefer, it is irrefutable that stock prices are determined by supply

and demand. Although new stock can be issued, for example when a company is wishing toraise new capital for fixed investment, stock prices at the overall equity market level are likelyto change from day to day because demand conditions are changing rather than because thenet supply of equity is increasing. If equity investors are feeling particularly confident, thenthey may well allocate more capital to stocks and this will push up prices. On the other hand,if equity investors are feeling much less confident, then they may well take capital out of thestock market and this will push down prices. If changes in the confidence levels of investorsare unpredictable, as seems the case empirically, then short-term price changes will tend tobe random.5 Of course, fundamental analysts will argue that the market or single stock hastemporarily moved away from fair value and recommend buying (if cheap) or selling (if rich).The technical analysts, on the other hand, will try to explain these short-term movements withreference to past price patterns.

1.1.5 Quantitative analysis

But what about the passive investors, those who judge that the future direction of pricemovements is unpredictable in all but the long run? Empirically, single equity prices andstock market indices tend to follow a pattern that closely resembles what mathematicians call

4 Although not recent, a 1988 NBER Working Paper, entitled What Moves Stock Prices?, found that “large market moves oftenoccur on days without any identifiable major news releases (which) casts doubt on the view that stock prices movements are fullyexplicable by news about future cash flows and discount rates”.

5 “I can predict the motion of heavenly bodies but not the madness of crowds”, Sir Issac Newton.

41



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Figure 1.1 S&P 500 historical prices

a random walk (with drift). Predicting future price changes over anything but the medium tolong term in such a world is likely to be unfulfilling. Investors can “predict” that they will earna long-run average return above the risk-free rate (since equities are risky) but the intermediatepath will be far from predictable. In this case, a single investor can only systematically “beatthe market” by being incredibly lucky. This is the world of the quantitative analyst. Put verysimply, quantitative analysts attempt to model the returns from assets, rather than their fairvalue prices since, empirically, price movements appear random but returns, over time, seemto follow something akin to a normal distribution (Figure 1.1).More recently, academics have suggested that, in fact, equity prices may more closely

resemble a first-order autoregressive process than a random walk. Without wishing to get toomired in mathematical-speak, such a process allows for mean reversion to the trend. If so, thenthere may be opportunities, after all, for savvy investors to beat the market. They just need tobe able to determine the trend!Neither the random-walk model nor the autoregressive model seems to be an entirely

accurate description of the process of equity price determination, however. Stock markets aremuch more volatile than such models would seem to imply. In particular, they do not seemfully to be able to explain the prevalence of stock market crashes.6 And, the models do notexplain why technical analysis has so many fans. If equity prices change with a random walk,then technical analysis is useless. If equity prices follow a first-order autoregressive process,however, then it may be possible to predict price moves from statistical analysis but the “head-and-shoulder” and “double-bottom” formations popular with technical analysts the world overare likely to be little more than colourful nonsense. As Simon Beninga suggests in his bookFinancial Modeling, “if you are going to be a technician, you have to learn to say these thingswith a straight face”.

6 Many quantitative analysts argue that, in practice, it is not worth trying to model crashes, for example. While they can createsignificant damage, there is very little that we can actually do about them. They may appear more regularly than the normal distributionwould imply but their prevalence still tends to be relatively limited. So, in practice, one can ignore them for modelling purposes aslong as one is also aware of them and tries to account for their effects.

42



So, why does technical analysis appear to work at some level? Perhaps because it has lots offans who follow the techniques and take investment decisions based on such. Is this rational,not entirely so but, then, humans are far from rational. How else can one explain the Dot-ComBubble?We have described the processes driving actual equity prices in some detail since those

same processes are at work in the other asset classes, most especially commodities, foreignexchange and indices. Fixed income products are much less easy to model, however.

1.1.6 The equity risk premium and the pre-FOMC announcement drift

The equity premium is the difference between the “average” return on the stock market and theyield on short-term government bonds. Most academic research into the size of the premiumfinds that it is too high to compensate for the average riskiness of equities. The equity premiumpuzzle is the name given to this phenomenon. Mehra (2008) provides a review of the literatureon this topic.7

A recent New York Fed staff report suggested that since 1994 more than 80% of the equitypremium on US equities was earned during the 24 hours preceding scheduled Federal OpenMarket Committee (FOMC) announcements (which generally occur just eight times a year).8

The researchers called this phenomenon the pre-FOMC announcement drift.The interesting aspect to note is that the pre-FOMC announcement drift is generally earned

ahead of the Fed’s announcement and so it is not directly related to the actual post-meetingmonetary policy actions. The historical record suggests that equity prices rise in the afternoonof the day before FOMC announcements and then rise even more sharply the next morning.Following the announcement, equity prices can vary widely but, on average, they tend to finishthe day around the same levels prevailing at the time of the announcement. In other words,unchanged. The gain over the 2 days as a whole, however, averages about 0.5%.On the other hand, since 1994, historic returns from equities are in line with the returns on

government bonds if thewindows around scheduled FOMCannouncement days are excluded.9

Note that similar patterns are found in other equity markets,10 although, in these cases,they are reacting to the FOMC announcements rather than announcements from their owncentral banks.Finally, while onemight expect similar patterns to be evident in other major asset classes, the

researchers concluded they were not. In other words, the pre-FOMC drift seems to be restrictedto equities.

1.2 COMMODITIES

1.2.1 Introduction

What is a commodity? The standard definition of a commodity is “any marketable itemproduced to satisfy wants or needs” and can include goods and services. For most of us,however, a commodity is essentially a basic resource that we use that comes out of the ground

7 See http://www.academicwebpages.com/preview/mehra/pdf/FIN%200201.pdf.8 See http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1923197.9 The return on the 24-hour period ahead of the FOMC announcement was about 3.9% per year, compared with only about 0.9%

per year for all other days combined. In other words, more than 80% of the annual equity premium is earned over the 24 hourspreceding scheduled FOMC announcements.

10 The FTSE 100, DAX, CAC 40, SMI, IBEX and the TSE.

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(e.g., wheat, corn, sugar, coffee, copper, aluminium, gold, silver, crude oil, natural gas, coal,diamonds, uranium, etc.). Obviously, this description is far from rigorous but it is intuitive.We can go one step further and say that soft commodities are grown, while hard commoditiesare extracted through mining or drilling.Commodities generally have actively traded derivative markets while the spot markets tend

to be less liquid. Themost active derivativemarkets are the commodity futures exchanges in theUSA and theUK, although the first real futuresmarket was probably the rice futuresmarket thatbegan in seventeenth-century Osaka, Japan. Spot markets provide for the immediate deliveryof the relevant commodity while the derivative markets provide for or accommodate deliveryat some point in the future; in some cases, as much as 10 years out. These markets help todetermine “world” prices althoughmost transactions in commodities do not actually take place“on market”. Instead, they are bilateral arrangements undertaken directly between a buyer anda seller. The prices at which these trades take place are generally not made public, since theyare private transactions, but they will tend to be determined to some extent in reference to theprices traded on the public markets.Most commodity products will have undergone some form of basic refining before they are

traded publically. For example, the copper that is traded on the LondonMetal Exchange (LME)is 99% pure, is in the form of cathode (a flat sheet of metal) and is quoted in lots of 25 tonnes(if one buys one lot, one is buying 25 tonnes of copper). Other commodities that will havegone through some form of refining include gasoline and fuel oil (both derived from crude oil),orange juice, lean hogs, sugar (refined from raw sugar), etc. Another important commodity iselectricity. Electricity is derived from other fuel sources (oil, coal, nuclear, renewables, etc.)and has the particular characteristic that it is uneconomical/difficult to store. Hence, electricityis produced as and when it is demanded/consumed.The main participants in the commodity markets are producers (mining companies, farmers,

refiners, oil companies, etc.), manufacturers (who use the raw materials to make consumerdurables and non-durables), households (who use electricity or gasoline), traders (who helpthe producers and consumers to hedge) and investors. Governments are also involved sincethey tend to intervene, perhaps to build strategic reserves in the case of the US government orto manipulate the price in the case of OPEC. We discuss the main participants in later sectionsdescribing their typical activity.11

Another aspect of commodities is that, although they tend to be lumped together under onesingle heading, there is no such thing as an average commodity. Their prices behave differentlyand they are influenced by commodity-specific factors. Gold prices will be impacted by thefestival season in India, oil prices by the driving season in the USA, Australian natural gasprices by tsunamis in northern Asia, global grain prices by droughts in the USA, Russia andAustralia, copper prices by earthquakes in Chile and coffee prices by the frosts in Brazil andColombia. As the global economy expands, we can assume that commodity prices will risebut the actual path of prices will be heavily dependent on the forces of nature.12

1.2.2 Hedging

Producers and consumers of commodities will use the derivative markets to hedge their futureproduction or consumption. Producers will want to lock in the prices of their future output

11 An excellent book on the real life world of commodities is The King of Oil, The Secret Lives of Marc Rich by Daniel Ammann.12 In the short run, prices will be volatile and this volatility will tend to outweigh the underlying growth rate. In the medium to long

run, however, prices will still be volatile but this volatility will tend to be outweighed by the underlying growth rate.

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so that they have certainty of revenue. This certainty is required since their capital spendingrequirements are enormous and spread out over many years. Likewise, consumers will lookto lock in the supply of raw materials over time since they will not want to risk not beingable to find the materials they need to manufacture their finished goods. This is hedging.The producers will generally sell their future output using prices determined today. They willdeliver their output at predetermined dates in the future and receive the price at the level settoday. The consumers will generally buy their future needs at prices determined today. Theywill receive the raw materials at predetermined dates in the future and pay the price at the levelset today.The hedging actions of the producers and consumers very rarely match. The producers tend

to hedge their output 3 to 5 years out while the consumers tend to hedge their demand outto 2 years. Moreover, the producers will tend to want to hedge when average prices are high(locking in high prices), while consumers will want to hedge when average prices are low(locking in low prices). Someone will need to sit in the middle, the speculators.The traders generally get a bad press from governments, regulators, consumer bodies and

charities since they are perceived as profiting from some kind of unfair activity in commodityprices. Such complaints are ill-targeted, however. Producers and consumers need to hedge.Without this hedging, producers and consumers would not be able to plan effectively. Bystepping in to offset the mismatch between the hedging activities of the producers and theconsumers, the traders are providing a publically undervalued service.

1.2.3 Backwardation and contango

Backwardation describes a situation where, for a given commodity, short-dated prices arehigher than longer-dated prices. For example, if the price for delivery of copper today is$8,000 per tonne and the price for delivery 5 years into the future is $6,000 per tonne, then thecopper curve would be backwardated. In this situation, one can argue that prices are assumed(or discounted) to fall over time (Figure 1.2).

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Figure 1.2 Backwardation curve

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Figure 1.3 Contango curve

In a curve that is in contango, short-dated prices are lower than longer-dated prices. Forexample, if the price for delivery of copper today is $8,000 per tonne but the price for delivery5 years into the future is $10,000 per tonne, then the copper curve would be in contango(Figure 1.3).Which curve shape is the natural state of affairs? When there is excess supply of a particular

raw material available, perhaps because the world economy is in recession and demand isweak, then the curve for that commodity may be in contango. Prices for immediate or near-immediate delivery will be low since producers will be happy to sell their excess inventories.Over time, however, producers will tend to cut back on their production, especially the high-cost producers. This will reduce the available supply, bringing supply and demand into balanceat higher prices. The commodity markets will anticipate this and so longer-dated prices, pricesfor delivery further into the future, will be higher than short-dated prices.When there is excess demand for a particular raw material, perhaps because the world

economy is booming and demand is strong, then the curve for that commodity may be inbackwardation. Prices for immediate or near-immediate delivery will be high since producerswill demand high prices for their production. Over time, however, consumers may switch tosubstitutes or completely alternative products. This will reduce demand over time, bringingsupply and demand into balance at lower prices. The commodity markets will anticipate thisand so longer-dated prices, prices for delivery further into the future, will be much lower thanshort-dated prices.13

The ability to store or warehouse commodities (with the notable exception of electricity)might suggest to the average market participant that the “normal” state of commodity curvesshould be gently upward-sloping, i.e., in gentle contango. If a particular commodity curve

13 Some commodity analysts interpret the long end of the commodity curve as a guide to the long-term marginal cost of productionfor that commodity. Empirically, when we look at forward curves at different points in time, long-term prices tend to cluster within asmaller range of prices.

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were too steeply upward-sloping and prices for the immediate or near-immediate deliveryof the commodity were much lower than longer-dated prices, then speculators could buy thecommodity, store it in a warehouse and simultaneously sell for future delivery at the higherlonger-dated price. Short-dated prices would tend to rise relative to longer-dated prices as theexcess supply was taken out of the market and stored. The profit from such a transaction woulddepend upon the difference between short-dated and long-dated prices, the cost of warehousingthe commodity (such as the rental cost of the warehouse and the insurance premium to insureit) and the interest cost of all the capital tied up in the commodity. Theoretically, then, there isa limit to the extent to which a commodity curve can be in contango.But what if the curve is in backwardation? In this case, traders who are holding inventories

may release their inventories in the spot market (i.e., for immediate delivery), selling at thehigh short-dated prices and buying back the inventory that has sold for future delivery at lowerprices. By not having to warehouse the inventories, they would save on warehouse rental, theinsurance premium and the interest cost of the capital deployed. Such flowswould tend to causea backwardated curve to move less into backwardation (or more into contango). The problemis that this trade cannot continue indefinitely. Once the available inventories have been soldoff, there will be pressure on the curve to return to the original extent of the backwardation. Itis easier to amass inventories than it is to keep selling them; once they have gone, they havegone. Hence, there is a limit to the extent of the contango but perhaps not to the extent of thebackwardation.Indeed, it is probably not an unreasonable statement to make to say that near-arbitrage

situations aremore likely to exist (and persist) in commoditymarkets than in other asset classes.This can occur for many reasons – for example, the activities of commodity consumers, theactions of index players in the futures markets, the inability to take advantage of the arbitrageopportunity (e.g., is there enough storage or transportation capacity?) and/or the inability toaccess sufficient finance.

1.2.4 Investment in commodities

The past 5 to 10 years have seen increased interest in commodities as a form of investment.Commodities are now demanded not just for the production of goods, say, but as a potentialsource of asset returns. Pension funds, insurance companies, sovereign wealth funds andwealthy individuals have been investing increasing amounts of money into commoditiespartly because they believe that commodity prices are likely to trend higher over time (asthe world demands more and more of these scarce resources) and because they are believedto offer portfolio diversification benefits relative to financial assets. Equity-like returns fromuncorrelated assets is the lure.At first, this investment took very simple forms, perhaps investment in a financial product

offered by one of themany investment banks involved in commodities. These financial productswere, and still are, often based on the average price of a basket of commodities. Later, investorsmight have moved onto slightly more esoteric products offered by these same banks or theymay have invested in one of themany commodity hedge funds that started in themid to late partof the last decade. Next, they might have invested in the underlying commodities themselves,possibly trading them on a public exchange. Finally, as their experience in commodity productsgrows, they might have invested in non-listed assets such as commodity-related infrastructure;for example, buying timberland, mines, agricultural land, refiners, etc.

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Note that the investment world has long been involved in commodities. Many investors havelong held equity in commodity producers and traders, such as the major oil producers (BP,Shell, etc.), the mining companies (Rio Tinto, Xstrata, etc.), commodity traders, electricityproducers and the like. For equity investment, however, the main risk tends to be the generallevel of the world’s major stock markets. The prices of commodity-related equities tend tobe highly correlated with the prices of equities issued by financials, utilities, producers ofconsumer goods and services, etc. So, investment in commodity-related equities tends tohave returns that are only indirectly related to commodity prices. This may explain whygovernments often complain about direct investment in commodities while not complainingabout investment in commodity companies, although this may be giving governments a littlemore credit than they perhaps deserve.The experience of many investors in the commodity sector has not been a rewarding one.

The early part of the last decade saw commodity prices rise rapidly, in large part due tothe industrial emergence of China and the other BRIC nations. Those investors who were infrom the start were able to ride the tremendous growth in prices in the 2000–2007 period.Those investors who became involved from 2007 onwards, encouraged by the gains of theprevious years, have lived through a very volatile period for commodity prices. The sought-after diversification benefits of direct commodity investment have not been as evident aspredicted since the financial crisis has, for example, hit commodity prices as much as it hashit equity and property prices. A number of high profile commodity hedge funds opened andclosed in this latter period as investors first flocked to them and then departed from them,discouraged by the extreme volatility of returns.Nevertheless, the amounts invested in commodities have continued to rise as more and more

asset managers look for ways to increase investment returns in the current low interest-rateenvironment.

1.2.5 Commodity fundamentals

Producers and consumers of commodities tend to think of commodity prices being determinedby demand and supply fundamentals and, on top of this, by investor flows. They tend not tothink of investor flows as being “real” supply and demand. One will hear statements suchas “copper prices are too high relative to supply/demand fundamentals”. Clearly, however,the current copper price is determined solely by supply and demand. That is how prices aredetermined. Commodity researchers will spendmuch of their professional lives analysing Chi-nese commodity imports, Chile’s copper output, cheating on production quotas by individualcountries within OPEC, maintenance schedules for oil rigs, weather patterns, etc. Then usingthese supply and demand fundamentals, they will forecast prices. In the past, commodityprices were much more stable and researchers tended to have more success in forecastingprices. With the recent increased volatility in prices, however, comes greater propensity forforecasting errors.The investment community is an easy target to explain those errors. “If it were not for

those pesky investors, prices would be lower”, might be one refrain from a researcher whohas under-predicted prices. Is this fair? Possibly, but perhaps one should ask why these sameresearchers are not trying to model the impact of investor flows, if investors do indeed have animpact (see below).One issue with commodity prices is that the demand and supply schedules are inelastic (in an

economics sense). Shifts in these schedules will have significant impacts on commodity prices

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Figure 1.4 Crude Oil WTI

and, unfortunately, these shifts are unpredictable and unobservable except through the prismof price changes. Could it be that unobservable movements in the fundamentals are really toblame for recent volatility of prices? After all, as demand increases with the industrializationof the BRIC economies and the rest of the newly industrialized economies (NIEs), there willbe a whole set of demand schedules that researchers know little about. This is especially thecase for China where the actual level of inventories is a multiple of the amount recorded inofficial warehouse statistics.The truth of the matter is that commodity prices are becoming more and more random in the

short term and this is not the fault of the investor. As commodity markets become tighter andtighter, with the growth of the NIEs and the depletion of the more easily accessible commoditysupply, one has to accept greater volatility in prices. This does not mean that the fundamentalsno longer apply. It just means that forecasting prices will become more and more difficult; asdifficult as forecasting FX or equity prices (Figure 1.4).

1.2.6 Super-cycles in commodity prices

A paper published in February 2012 by the United Nations’ Department of Economic andSocial Affairs14 reviewed the literature around super-cycles in commodity prices.

What are super-cycles? They are decades-long periods of significantly above- or below-trendmovements in prices. Super-cycles differ from short-term fluctuations that come about frommicroeconomic factors in that they tend to span “20–70 year complete cycles”. These longcycles can see commodity prices varying between 20 and 40% above or below their long-runtrend. The authors of the UN report argued that approaching the analysis of commodity pricesfrom a super-cycle framework is “an important innovation over the more traditional analysis

14 http://www.un.org/esa/desa/papers/2012/wp110_2012.pdf.

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of trends and structural breaks (since) it allows us to analyze the gradual change in long-termtrends instead of a priori assuming a constant deterministic or stochastic trend”.15

1.2.7 Future regulation

Although evidence to support the view that direct investment in commodities leads to higherprices is patchy, there is a belief among many that those people who do not directly usecommodities in the production process should not be allowed to buy them since these peopleobviously (sic) push commodity prices higher than they otherwise would be to the detrimentof all. As noted earlier, however, many traders, especially those who help producers andconsumers to hedge, provide a very valuable service. Hence, there is a begrudging acceptanceof such activity although it is still viewed with suspicion by some politicians, regulators,charities and consumer bodies.Investment in commodities to turn a profit, however, wins few fans outside of the investment

business despite there being conflicting evidence as to whether or not investors themselvespush up prices. A review by the last Labour government in the UK found that investmentflows did not impact commodity prices on average but did increase the overall liquidity of themarketplace while a recent study by the Commodity Futures Trading Commission (CFTC)found that investor flows were the main determinant of the moves in agricultural futures pricesin the USA.Consider the case of commodity futures markets, however. If investors are buying, someone

must be selling since futures contracts are a zero-sum game. The buyers always equal thesellers. Are the investors merely hedging producer supply? To be fair, much of the work donein this area tends to be politically motivated and, as such, the results will have a politicalbias. Interestingly, when prices are rising, the investor tends to get the blame, when prices arefalling, however, it is the state of the world economy. Nevertheless, the upshot is that investorsin commodity futures will find themselves more and more limited in what they can and cannotdo. Some regulators would clearly like to be in a position where only “real” commodity peopletrade commodities even if liquidity is harmed in the process.

1.3 FIXED INCOME

1.3.1 Introduction

Fixed income products can be split into three broad categories, rates, credit and inflation.For all these, a significant driver of the equilibrium price of the product will be the generallevel of interest rates, as determined in a large way by the relevant central bank. For ratesproducts (government bonds and interest rate swaps), changes in the general level of interestrates are essentially the only significant driver of equilibrium prices. Credit products, however,are those where there is a second, significant driver of prices, i.e., credit risk – for example, inthe case of a bond issued by a highly-geared corporate or by a lowly-rated emerging marketsovereign (in the last few years, credit risk has become a major factor also in the sovereignbond market of some Euro Zone countries). By extension, inflation products are those where

15 As an aside, the authors also note that there is a short-run relationship running from crude oil prices to changes in world output.This finding supports the widely held view that oil price hikes constrain economic growth in the short run. This is in sharp contrastwith non-oil prices, which tend to follow world GDP and are thus more demand determined.

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the second significant driver of prices is the future development of some inflation index, suchas Consumer Price Index (CPI) or Retail Price Index (RPI) – for example, in the case of aninflation-linked bond issued by a sovereign or the case of an inflation swap offered by aninvestment bank.Fixed income products may also be thought of as flow or structured. Flow products are

essentially those products that are traded by many market participants and they have simplercash flow structures. A flow product, for example, would be a government bond, a bondissued by a corporate or an interest rate swap (we discuss swaps in some detail later in thebook). Structured products, on the other hand, are essentially those with relatively complex,non-linear cash flows, although, with the passage of time, the distinction between what is flowand what is structured has become a little blurred. Products that were once considered to bestructured are now thought of as flow, such as Credit Default Swaps (CDS), Mortgage BackedSecurities (MBS) or basic options.

1.3.2 Credit risk

Credit risk is the risk that a borrower will not be able or willing to meet its interest or principalrepayment obligations. Historically, the risk for many borrowers has been assessed by ratingsagencies, such as Standard and Poor’s or Moody’s. Each of the ratings agencies has a slightlydifferent approach to valuing credit risk, although their qualitative assessments tend to bevery similar.How does one measure credit risk? There are many ways to measure credit risk depending,

to some extent, on how the enquiry is framed. In simple terms, however, credit risk can bethought of as the probability of a credit event occurring (e.g., a default) multiplied by the lossincurred as a result of that credit event.16 Credit events include bankruptcy, failure to pay,default or repudiation (a polite term for sovereign default).As noted above, for all fixed income products, one would expect their prices to be influenced

directly by the general level of interest rates. However, credit risk (and inflation) will also beimpacted indirectly by the level of interest rates. As interest rates are reduced, for example,one would expect that the ability of a borrower to meet his or her obligations will improve,i.e., credit risk would decline. On the other hand, if interest rates are increased, one wouldexpect the ability of the same borrower to meet his or her obligations to deteriorate, i.e., creditrisk would increase. In a sense, the prices of credit products are influenced both directly andindirectly by the overall level of rates and by factors related to the specific borrower.

1.3.3 The empirical pattern of yield curve moves

Until 2010, the historical record showed that yield curves bull steepened or bear flattened.17

When yields fell, they tended to fall across the entire yield curve and to be led by movesin short-tenor instruments. Not only that but the absolute moves in short rates were greaterthan the absolute moves in long rates, hence, the yield curve steepened. Conversely, when

16 Credit risk (or spread) = probability of default × (1 – recovery rate). What you expect to lose multiplied by the probability thatyou will lose it.

17 Since the start of 2010, central banks around the world have held short-term interest rates at very low levels as they have triedto combat the balance sheet recession. With short rates held in place, interest-rate volatility that would usually manifest itself alongan entire yield curve has been transmitted into the medium to long end of the curve. Consequently, higher yields have tended to beassociated with steeper (rather than flatter) curves and vice versa for lower yields. This pattern is likely to remain the case until thecentral banks refrain from holding short rates at abnormally low levels.

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yields rose, they tended to rise across the entire yield curve and to be led, again, by movesin short-tenor instruments. Again, the absolute moves in short rates were greater than theabsolute moves in long rates and, hence, the yield curve flattened. At the same time, however,yield curves would see significant changes in their shape. As rates fell, they tended to becomemore convex (imagine an upside-down bowl). As rates rose, yield curves tended to becomeless convex and more concave (imagine a normal bowl).The key driver in most cases was central bank activity. If central banks are in control of

anything, it is short-term interest rates. Short rates are raised and lowered in order to controlmacroeconomic variables. As short rates are changed, the entire yield curve follows but longrates typically move by less; they tend to be more stable.

1.3.4 Modelling interest rate movements

Modelling stock or commodity price movements is relatively easy; assume a random walk,with an element of mean reversion and some capacity for occasional (random) jumps to“explain” market crashes. Modelling interest rates is a lot more complicated, however. In fact,we include this section (and the next) for completeness but most readers will probably preferto skip it (them) and move straight to the section on foreign exchange.In Quantitative Finance, Paul Wilmott notes, “ . . . there’s no reason why interest rates

should behave like stock prices, there’s no reason why we should use the same model forinterest rates as for equities. In fact, such a model would be a very poor one; interest ratesdo not exhibit the long-term exponential growth seen in the equity markets.” A thoroughdescription of the leading interest rate models is beyond the scope of this book but interestedreaders may want to take a look at Rebonato’s classic Interest-rate Options Models.In the jargon, interest rate models either attempt to model the future movements in a liquid,

“short rate”, such as the Ho & Lee approach, or they attempt to model movements in the entireforward curve,18 such as the Heath, Jarrow & Morton (HJM) approach. When modelling thepath of the short rate, this will be something like a 1-month or 3-month rate rather than theovernight rate since changes in the latter tend not to be a very good guide for other short-termrates. Just as with modelling equity or commodities, the interest rate modeller will need a“drift” parameter, i.e., by how much will interest rates tend to change from period to period,and a “volatility” parameter that measures the random changes in interest rates around thedrift. Unlike models for equities and commodities, however, there will also need to be meanreversion to some kind of constant value (rather than to a trend). Finally, if one can model thefuture path of the spot rate, then one can, of course, create an entire yield curve.

1.3.5 Modelling the risks of default

When modelling default, it is generally assumed that the probability of default is exogenousto the asset under consideration. Such an approach is popular since it is simple to use even ifit does not sound very clever. Think about simultaneously tossing three coins every month. Ifyou get three heads, then assume default.Now think of a corporate bond and a risk-free bond of equal maturity. In the world just

described, where the risk of default is exogenous, the incremental yield that the corporate bond

18 Forward rates are those future short-term interest rates implied by the current yield curve.

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needs to earn to compensate for the default risk can be thought of as a fixed spread added tothe yield on the risk-free bond.19

For example, a 5-year risk-free bond has a yield to maturity of 6%while the yield to maturityof a 5-year risky bond is 7.5%. The extra 1.5% is the compensation for the risk of default. Inthis example, if we have 100% loss at default, then the implied probability of the companydefault is approximately 1.5% per year.A slight refinement to this model is to assume that the probability of default changes with

time. For example, one could assume a Poisson distribution so that there is a very small chanceof a default initially, rising over time to some maximum value before tailing off indefinitely.This seems to mirror the empirical record. Over the long term, companies either do well orhave already gone bust; it is unusual for well-established companies to go into default, theyare generally taken over beforehand.In practice, loss on default is not 100% and there is usually some recovery value and one

can assume a recovery value given the historical record. Such data is easily obtained fromthe ratings agencies. Of course, alternatively, the recovery rate could be modelled but this isprobably a digression too far.Finally, as an aside, we note that there is the possibility of a re-rating, either positive or

negative. The ratings agencies publish data on the likelihood of transition from one rating toanother and this data could also be incorporated into models to price credit risk.

1.4 FOREIGN EXCHANGE

1.4.1 Introduction

An exchange rate is the ratio of the price of one currency versus another. In most cases,exchange rates between the currencies of the developed economies are freely floating althoughthere are occasional bouts of central bank intervention.Empirically, the best forecast of tomorrow’s exchange rate is today’s spot rate. In other

words, short-term changes in exchange rates tend to be random. This does not cause too muchworry for the FX forecasting profession, however, which makes a great living from makingshort- and long-term forecasts. As with equities, there is fundamental analysis, technicalanalysis and quantitative analysis.There are many fundamental models of exchange rates. Unfortunately, despite the efforts of

many academic researchers in particular, such models fail to explain the following real worldexperiences:

1. Exchange rate movements very often tend to be unrelated to changes in macroeconomicvariables over periods exceeding a year.

2. Exchange rates are excessively volatile relative to the underlying economic fundamentals(assuming that we can agree on what these are).20

19 The spread to the risk-free rate is not all credit risk. There are other issues to take into account such as the relative liquidity ofthe credit bond versus the risk-free bond but, as a means of understanding, it is probably a fairly reasonable approximation.

20 A 2011 IMF Working Paper argued that inflation and growth rates are the two principal fundamental factors used by foreignexchange forecasters in the formation of exchange rate expectations. The prominence of inflation points to broad acceptance ofpurchasing power parity. Other oft-mentioned factors, including the current account balance, do not appear to play a common role inthe formation of exchange rate expectations. See http://www.imf.org/external/pubs/ft/wp/2011/wp11116.pdf.

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Note also that excess returns (i.e., returns over and above the risk-free interest rates) fromspeculating in currencies tend to be predictable but inexplicable; what academics call theforward bias puzzle.Given the weaknesses inherent in fundamental analysis of exchange rates, it is surprising

that it is still popular, although, of course, we all like to have some kind of prop to supportour decision-making. When the forecasts support the investment view, they are popular. Whenthey do not support the investment view, they can be ignored.Technical analysis is also very popular for foreign exchange markets, perhaps because the

fundamental models have such a poor forecasting record. Nature abhors a vacuum and it ishuman nature to try to explain the world through repeated patterns. There are many adherentsand some techniques within technical analysis do seem to work for foreign exchange forecastsbecause of this. If enough market participants expect a certain exchange rate level to hold,then it will very likely hold. The problem is, we tend to remember the successes morethan the failures and most testing of the value of technical analysis tends to be undertakenin hindsight.Surveys of foreign exchange market participants suggest that they generally base their

short-term forecasts on recent trends, i.e., they extrapolate recent behaviour. This is whymoving averages are so popular as technical analysis tools. Moving averages are essentiallyextrapolative, i.e., they extrapolate the recent trend. Longer term, however, i.e., 1 to 2 years,market participants tend to focus more on fundamental models in their assessment of value.Nevertheless, foreign exchange trading tends to be short-term trading, given the sensitivity ofmost players to large mark-to-market swings. As a consequence, while fundamental modelsmay matter, they have little relevance for near-term price developments.

1.4.2 How foreign exchange rates are quoted

Foreign exchange rates are always defined in currency pairs, e.g., EUR/USD. The first currencyin the pair is called the base currency and the second is called the term currency. The foreignexchange rate represents the number of units of the term currency that must be surrenderedin order to acquire one unit of the base currency. So, a foreign exchange rate defined asCCYA/CCYBand equal toXmeans thatX units of theCCYB (term currency) can be exchangedfor 1 unit of CCYA (base currency). In other words, if the EUR/USD rate is 1.27, it meansthat 1.27 units of USD can be exchanged for 1 unit of EUR.When expressing foreign exchange rates against USD, the standard market conventions are

as follows:

∙ When quoting EUR, GBP (Great Britain pound), AUD (Australian dollar) or NZD (NewZealand dollar) against USD, the USD is the term currency. Consequently, the standardmarket convention is to quote EUR/USD, GBP/USD, AUD/USD or NZD/USD respectively,i.e., number of US dollars per unit of the other currency.

∙ When quoting the remaining currencies against USD, the USD is the base currency. Con-sequently, the standard market convention is to quote the number of units of the foreigncurrency per 1 US dollar, e.g., 1 USD = 0.89 CHF in the case of Swiss franc.

∙ When quoting EUR crosses, EUR conventionally tends to be the base currency, i.e., onewill generally see market prices such as EUR/AUD, EUR/CHF, EUR/JPY (JPY is theJapanese yen).

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SUMMARY

In this chapter, we focused on the liquid investment asset classes in which financial derivativesare normally traded, namely equities, fixed income, commodities and foreign exchange. Theaim was to give a sense of the general price characteristics of these markets, e.g., how they arequoted and how they move through time. We also aimed to make some observations on howto model underlying asset price behaviour for each asset class since investors must understandhow prices behave in their composite parts in order to have a real understanding of the valuethat can be extracted from multi-asset derivative products.

Project Risk ManagementEssential Methods for Project Teams and Decision MakersYuri Raydugin 978-1-118-48243-8 • Hardback • 400 pages • October 2013

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£50.00 £30.00 / €60.00 €36.00 / $75.00 $45.00


56

I PART ONE

Fundamental Uncertainty of a Project Outcome

IN WORDS AT TRIBUTED TO Abraham Lincoln, Peter Drucker, Steve Jobs, and several other prominent individuals, the best way to predict the future is to create it. Project development could be understood as an activity to pre-

dict future project outcome through creating it. The role of risk management is to ensure a certain level of confi dence in what is supposed to get created as a result.

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HTED M

ATERIAL

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3

1 CHAPTER ONE

Nature of Project Uncertainties

MULTIPLE FAC TORS INFLUENCE OVER ALL project outcome. Their nature and infl uence depend on how a project is developed and executed, what are project objectives and expectations of stakehold-

ers, and so on. It is not possible to manage factors infl uencing project outcome without properly understanding their defi nition. Only when all relevant uncer-tainty elements are pinned down and all factors leading to uncertainty changes

Questions Addressed in Chapter 1

▪ What could be expected as a project outcome? ▪ What factors are behind deviations from the expected project

outcome? ▪ Do we really know what we try to manage? ▪ What degrees of freedom do uncertainties have? ▪ What are major uncertainty objects and their changers? ▪ When is a decision really a decision and when it is an opportunity? ▪ Is it really risk management? Or is it actually uncertainty

management? ◾

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4 ◾ Nature of Project Uncertainties

are clearly understood can a minimal set of adequate methods be selected to manage all of them effectively.

Those multiple uncertainty elements are called uncertainty objects in this book. Systematic defi nitions are proposed for all of them from fi rst principlesbased on the intrinsic nature of project uncertainties along with main factors that change the objects ( uncertainty changers ). The purpose of these defi nitions is not to come up with linguistically fl awless descriptions of the objects, but to refl ect on their intrinsic nature. The degrees of freedom are used to classify various realizations of uncertainties. This formalized systematic consideration, which resembles symmetry analysis of physical systems, is converted to spe-cifi c and recognizable types of uncertainties and changers that pertain to any capital project.

PHASES OF PROJECT DEVELOPMENT AND PROJECT OBJECTIVES

Phases of project development used in industries vary as do their defi nitions. They are also different in the same industry, for instance, in the case of project owners and contractors. We will use a simplifi ed set of project phases that is common in the oil and gas industry in the owner environment (see Table 1.1 ).

The fi rst three phases are often combined to front‐end loading (FEL). They precede fi nal investment decision (FID), which is supposed to be made by the end of Defi ne, which is a crucial point for any project (no FID, no project’s

TABLE 1.1 Project Development Phases

Project Phase Description

Identify Commercial and technical concept is pinned down; its feasibility is considered proven by the end of Identify.

Select Several conceptual options are outlined; one is selected for further development by the end of Select.

De� ne Selected option is developed, including all baselines; it is sanctioned by the end of De� ne [� nal investment decision (FID)].

Execute Approved project is being implemented and completed by the end of Execute.

Operate After commissioning and startup, project is in operations during its lifetime and decommissioned by the end of Operate.

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Quest for Predictability of Project Outcome ◾ 5

future). All project objectives and baselines are supposed to be well developed prior to FID to be reviewed and (hopefully) sanctioned.

The main focus of this book is on phases preceding FID (i.e., on FEL). For this reason two main project lifecycle periods could be introduced conditionally and told apart: “Now” (FEL) and “Future.” Operate certainly belongs to Future, which could include dozens of years of project lifetime before decommissioning. Execute seems to hide in a gray area since it’s the beginning of Future. It starts at FID and doesn’t end until the project is complete. One could imagine the high spirits of a project team, decision makers, and project stakeholders when a project FID is made and announced. The boost in energy, enthusiasm, and excitement following the positive FID is certainly an attribute of a “Now‐to‐Future quantum leap.”

After positive FID a project is likely to have future. So, decision makers, team members, and stakeholders are interested in knowing what sort of actual future characteristics it might get upon completion. If we regard project objec-tives and baselines as a sketchbook put together for FID, how close would the original (i.e., project completed in Future) resemble sketches done Now?

The answer to this question becomes clear in the course of project execu-tion. By the end of Execute there will be a pretty clear picture. The original could appear even more beautiful and attractive than the sketches of the past. This is a sign of the project’s success. But the original could also get ugly, with sketches being quite irrelevant to reality.

To continue the artistic analogy, the sketches may be done using vari-ous styles and techniques. The variety of styles could resemble anything from cubism, expressionism, and pop art, to impressionism, to realism. (Guess what these styles could mean in project management!) A “project development style” adopted by a project in FEL depends on many factors: from maturity of the company project development and governance processes and biases of team members and decision makers, to previous project development experience, to stakeholders’ expectations and activism. But what is even more important is the “project execution style.” Its abrupt change right after FID could make pre‐FID sketches completely irrelevant (see Figure 1.1 ).

QUEST FOR PREDICTABILITY OF PROJECT OUTCOME

Figure 1.1 represents a concept of a value associated with project defi nition and execution. The term defi nition means here all activities related to FEL, and not only to the Defi ne phase, whereas the term value could be perceived as an

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amalgamation of project objectives, baselines, and stakeholders’ expectations compared with the completed project. (In a simplifi ed interpretation it could relate to either project cost or duration.) According to Figure 1.1 , a project value may be characterized by a broad spectrum of outcomes, from unconditional success to complete failure. According to benchmarking data and the defi ni-tion of project failure by the IPA Institute, a staggering 56% of major projects fail due to

▪ Budget overspending for more than 25%, and/or ▪ Schedule slipping for more than 25%, and/or ▪ Severe and continuing operational problems holding for at least one year. 1

Imagine what the failure numbers would be if we used 15 or 20% thresholds instead.

Project defi nition and execution is a battle against multiple factors of uncer-tainty of the project outcome. Multiple uncertainties and deviations from proj-ect objectives should be understood as inputs to project defi nition and execution that drive overall uncertainty of outcome. Depending on features of project development and execution, this could be either an uphill or downhill battle. Accumulated deviations from multiple project objectives and baselines upon

FIGURE 1.1 Project De� nition, Execution, Value, and Outcome

Project Value

Good Definition

Poor Definition

Identify Select DefineFID Startup

Execute Operate

Poor Execution

Good Execution

Good Execution

Good DefinitionVs.

Good Execution

Poor DefinitionVs.

Good Execution

Good DefinitionVs.

Poor Execution

Poor DefinitionVs.

Poor Execution

Poor Execution

Time

Unc

erta

inty

of P

roje

ct O

utco

me

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Sources and Types of Deviations from Project Objectives ◾ 7

project completion could be both favorable and unfavorable to various degrees. Decision makers, project team members, and stakeholders have a vested inter-est in the fi nal outcome of a project. Was this delivered within scope and quality, according to the sanctioned budget and by the approved completion date, or was the discrepancy between baselines and reality appalling? Were changes done during project development and execution? Were they properly taken into account? What was the safety record or environmental impact in the course of project delivery? Has the owner’s reputation suffered?

All these questions emphasize multiple dimensions of project goals and uncertainty of project outcome. All project disciplines—engineering, procurement, construction, quality, project services, safety, environment, stake-holder management, and so on—take part in shaping corresponding baselines and managing multiple uncertainties at the work package and project levels. Project risk management has unique positioning, though. It not only evaluates the credibility of all project baselines but must identify and manage deviations from them in all their thinkable realizations due to multiple uncertainties.

SOURCES AND TYPES OF DEVIATIONS FROM PROJECT OBJECTIVES

Multiple uncertainty factors give rise to the overall project outcome and, hence, to deviations from the initially stated project objectives and baselines. A com-bination of all particular deviations from objectives in the course of project development and execution contributes to the overall uncertainty of the project outcome.

Any project objectives or baselines, such as project base estimates, sched-ules, or engineering design specifi cations, are models that try to mimic future project reality. As mentioned in the Preface, each such model may be character-ized by its distance to reality . 2 It would not be an exaggeration to say that those baselines have quite a large distance to reality by default. All of those baselines are developed in a perfectly utopian uncertainty‐free world. For instance, all costs, durations, or performance parameters are one‐point numbers , imply-ing that they are fully certain! Such a wonderful level of certainty could be achievable only if all stakeholders of a project welcome it North‐Korean style; all subcontractors and suppliers cannot wait to ensure the highest possible quality and just‐in‐time delivery, demonstrating Gangnam‐style excitement; technology license providers and fi nancial institutions greet the project by per-forming Morris dancing enthusiastically; and regulatory bodies are engaged

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in encouraging Russian‐Cossack‐style dancing. It is a nice, utopian picture of a project environment (although those dances more often resemble daily Indo‐Pakistani border military dancing of carefully choreographed contempt).

All those multiple uncertainties give rise to multiple deviations from the utopian risk‐free baselines shaping the project reality. Let’s introduce a set of standard project objectives in this section as well as reviewing the reasons for deviations from them that are observed in any capital project. Tradition-ally, three project objectives have been considered (triple constraint, iron triangle, etc.):

1. Scope/Quality/ Performance2. Capital expenditure budget (CapEx)3. Schedule

These three objectives imply constraints on each other to exclude apparent dichotomies, as fast delivery of a good project cheaply is not quite possible.

First, there should be a reason for undertaking a project. This should bring up a certain level of utility in Operate. Usefulness of a capital project could relate to characteristics of a structure to be constructed (a building of a certain size and purpose, a bridge of expected load rating, etc.) or to performance of a production facility of a certain production output (barrels of oil or cubic feet of natural gas produced and/or processed per day, tons of fertilizer produced per month, tons of carbon dioxide captured and sequestered in aquifer per year, etc.). Both structures and production facilities should be durable enough in the course of their operations, which brings up topics of reliability, availability, and maintainability.3 A budget for operating and maintaining a facility (operat-ing expenditure budget—OpEx) should be reasonable economically to support the required level of reliability and availability and, hence, planned operating income. The Scope/Performance/Quality objective is the first of the classic triple constraints. There are many uncertainty factors that could lead to deviations from this objective.

Second, a structure or facility of concern should be delivered according to an approved capital expenditure budget (CapEx). A base estimate of a project takes into account all required expenses to deliver it. Needless to say, accu-racy of the base estimate depends on phase of project development. The level of engineering development is a major driver of accuracy for every cost account. For instance, when developing a concept design of a production facility, the amount of pipes of small (few inches) diameter is not quite clear. To estimate inevitable additional expenditures that will be justified later, corresponding

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design allowances are used to address uncertainties related to material takeoff. If a project is unique and adopts a new technology, the required design allow-ances could be quite high. In the case of repetitive projects it could be just a few percentage points of corresponding base estimate cost accounts.

Each work package could have an estimate of specific accuracy level in a given phase. Besides level of engineering development, accuracy of a package estimate strongly depends on progress of procurement activities, with highest accuracy expected when the prices are locked in. Nobody doubts that there will be the price of, say, construction materials in the base estimate of a given project. (Formally speaking, the probability of the presence of this cost in the base estimate is exactly 100%.) It is usually questionable which particular price it would be. Moreover, if several estimators are asked to prepare an esti-mate of a project or its work packages independently, no doubt there will be a visible spread of their numbers. Differences in the estimate numbers could be explained by variations of historic data and methods used for estimating as well as the personal experience and qualifications of the estimators. Some of them are more aggressive (optimistic) by nature and some are more prudent (pessimistic). The latter example is one of the realizations of psychological bias in project management that will be discussed in this book, which is also realiza-tion of a general uncertainty.

A base estimate is normally developed in the currency of a base period. One dollar (or ruble, yuan, dinar, yen, euro, and so on) today won’t have the same purchasing power several months or years from now when estimated items will be actually purchased. The issue here is not just general inflation, which is normally equal to a few percentage points per year in North America. General inflation, which is usually measured as consumer price index (CPI), has almost nothing to do with future prices of line pipes or structural steel, or the cost of labor in Texas or Alberta. For example, prices of several types of line pipes grew 20–40% in 2008 before dropping drastically by year‐end. Supply–demand imbalances in particular industry segments could exceed CPI manifold.

Cost escalation is a special type of general uncertainty that could be pre-dicted relatively adequately using the correct sets of macroeconomic indexes. Obviously, prices do not rise indefinitely. Drops in prices of materials, equip-ment, and services used by capital projects could be significant. Cost de‐escala-tion could be predicted and used for selecting the right purchasing time. These last two statements could generate some skeptical remarks. To “predict” here means to forecast the general upward or downward trend of prices in a particu-lar segment, not an absolute level of prices. For instance, existing escalation models for line pipes based on right macroeconomic indexes forecast annual

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growth of around 10–15% in the first three quarters of 2008. It was much less than actual growth, but informative enough for sober decision making.

If some materials or services are purchased abroad, currency exchange rate volatility causes additional uncertainty in the CapEx. It could be man-aged similarly to cost escalation/de‐escalation. The capital expenditure budget (CapEx) objective is the second of the three traditional constraints.

As a project is supposed to get delivered not only on Scope and on Cost but on time, too, the third classic constraint is Schedule, meaning project duration. A schedule developed as a project baseline has a completion date, not a range of dates. Similarly, all normal activities of the schedule will have unambiguous one‐point durations. Is it too bold to state certainty like this? Of course, actual durations of most (if not all) of the normal activities will differ from the model. The Schedule is just a model that has its own distance to reality, too. The real project completion date will differ from the planned one. I recall several occasions when mega‐projects developed behind the Iron Curtain were completed right as declared, which had deep political and repu-tational meaning back then. All of those projects were complete disasters in terms of CapEx, and especially Scope/Quality/Performance, though. My recent experience points to the fact that this can happen on both sides of former Iron Curtain.

Again, the level of project development (especially engineering and pro-curement development) as well as methods and data used for planning are major drivers of duration general uncertainties. We know there will be a dura-tion for a particular normal activity. We just don’t know exactly what the dura-tion would be. Similar to estimating, if several schedulers take on schedule development independently, durations of normal activities and overall project durations would not be the same, bringing up corresponding spreads. Again, different historic information and methods could be applied by different sched-ulers who themselves could have different levels of experience, expertise, and aggressiveness. Moreover, schedule logics proposed by different schedulers could differ.

It is obvious that if an engineering or construction team is deployed to deliver a particular project, there will be incurred costs in case of schedule delays. Construction crews, engineering teams, rented equipment or buildings, and so on should be paid for no matter whether those work or stay idle. This brings up an additional general uncertainty factor that should be taken into account to assess schedule‐driven costs, or rather, schedule‐delay‐driven cost impacts. We will use “burn rates” that may be treated as general uncertainties to integrate probabilistic cost and schedule analyses.

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The deviations from the three classical project objectives described ear-lier are actually part of “business as usual,” being attached to Scope, Cost, or Schedule baselines. No unexpected factors or events that are not part of base-lines are contemplated. However, in place of precise baseline one‐point values we actually assume ranges of those values. In an attempt to reflect on this ambiguity, project engineers, estimators and schedulers introduce the most reasonable or likely representatives of those scope, cost, and schedule ranges as one‐point values surrounded by an entourage of the other values from the ranges. Obviously, the spread associated with the existence of the entourage relates to an ambiguity of possible impacts on objectives, and not probabilities of the impacts. There is no uncertainty associated with the impact’s existence that is absolutely certain. Let’s call those one‐dimensional uncertainties of just impact ambiguity general uncertainties.

However, myriad unplanned events might occur in a real project. If they occur, those could be seen as “business unusual” as they are not part of base-lines at all. Probabilistic methods allow one to take those uncertain events into account but outside of baselines and through attaching to them probabilities of occurrence. Project delays related to the permitting process or additional requirements related to protection of the environment that are imposed as con-ditions of project approval by the government are examples of uncertain events that impact Scope, Cost, and Schedule objectives. However, their exact impacts and probabilities stay uncertain. Being associated with business unusual, they have not one, but two dimensions of uncertainty, both uncertainty of impact and uncertainty of occurrence. Let’s call the business‐unusual events uncertain events.

However, uncertainty of impact means general uncertainty. Hence, general uncertainty merged with uncertainty of likelihood gives rise to an uncertain event.

Mathematically, general uncertainties may look like a subclass of uncertain events when probability gets to 100%. Technically, this is correct. However, our previous discussion on “business as usual” versus “business unusual” dic-tates to tell them apart. Philosophically speaking, when an uncertain event is losing one dimension of uncertainty becoming absolutely certain in terms of happening (100% chance of happening), it redefines the whole nature of the uncertainty as the “game of chance” is over. It’s like gambling in Las Vegas and knowing for sure that you will beat the wheel every time it spins. Unclear would be only the size of each win. How can a casino profitably operate like that?

What technically happens when an uncertain event actually occurs? In place of probability of a possible deviation from project objectives equal to, say,

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5%, the deviation suddenly becomes a reality. It becomes a fact or given with probability of 100% as no game of chance is involved anymore. This directly leads to impact on project objectives. As an uncertain event loses one uncer-tainty degree of freedom it becomes a general uncertainty if its impact is not yet fully understood. When the impact of that former uncertain event that turned to a general uncertainty eventually becomes known, it becomes an issue and redefines project baselines. An issue loses both characteristics of uncertainty. It is certain in terms of both likelihood (100%) and impact (no range/one‐point value).

If an uncertain event has occurred, it is too late to proactively prevent this. The only way to address this is to try to screen out impacts on project objectives through some recovery addressing actions. This should be considered part of reactive crisis management. Ideally those reactive actions should be planned beforehand for cases in which risk prevention does not work. Crisis manage-ment is usually more costly than preventive actions. An ounce of prevention is worth a pound of cure!

Imagine a situation where an uncertain event characterized by a probabil-ity of occurrence has a clear impact without any impact range. It would belong to the category of discrete uncertain events in terms of impact when impact on or deviation from objectives is fully predictable. For instance, in the case of circus equilibrists who are working without a safety net, the probability of failure is quite low although the possible safety impact is rather certain.

Some uncertain events could have very low probabilities and extremely high impacts. So, they cannot be viewed as moderate deviations from project objectives. Their possible impacts might be comparable in magnitude with baselines. Being in the same or higher “weight categories” with baselines, nat-ural disasters, some force majeure conditions, changing regulations, opposition to projects, general economic crises, and so on could lead to devastating scope changes, critical cost increases, and knockout schedule delays. In a sense, those events destroy initial baselines or fully redefine them. For instance, if a pipeline project that had an initial duration of two years was delayed due to opposition and strict environmental requirements for three years, all its initial baselines should be redone. Moreover, the project owner might just cancel the project and pursue some other business opportunities. Eventually, if approved and moved forward, it will be a different project with different scope, cost, and schedule.

Uncertain events like this are called “show‐stoppers” (a knockout blow on objectives), “game changers” (a knockdown blow on objectives), or “black

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swans” among risk practitioners.4 Despite the fact that those are part of enterprise or corporate risk management (ERM), they should be identified, monitored, and reported by the project teams. A project team cannot effectively manage events like this unless a sort of insurance coverage is contemplated in some cases. The owner’s organization should assume ownership of the show‐stoppers and game changers in most cases. For this reason, such supercritical project uncertain events are also called “corporate risks.”

Using some analogies from physics, we may compare baselines with base states of a physical system. For instance, a crystal lattice of a solid matter at zero degree Fahrenheit represents its base state. If temperature slightly increases, linear vibrations of atoms around their equilibrium positions take place. Those independent small deviations from a base state are called pho-nons. Degrees of deviations are relatively small and don’t disrupt the base state. We may conditionally compare those linear vibrations with general uncertainties. However, if temperature further rises, some new nonlinear effects occur when phonons are examined as a population or superposition of quasi‐particles. Their collective behavior gets clear statistical features. In some situations this behavior modifies characteristics of the solid matter. We may compare this with correlated uncertain events. If temperature further increases, the energy of the population of phonons, which obtain clearly non-linear behavior, could be enough to change the base state. Phase transition occurs, leading to a change in crystal lattice type. Isn’t this a game changer? If temperature further increases and reaches the solid’s melting point, there is no solid matter anymore. This sounds like a show‐stopper in the case of corporate risks. Moreover, some impurities or defects of a crystal lattice that are not expected in ideal solid matter could be compared with some unknown uncertainties.

We don’t want to exaggerate the depth and significance of this analogy between solid state physics and project risk management. However, it could be informative for readers with a technical background.

Besides the traditional triple constraint objectives, organizations use addi-tional project constraints these days. For example, a project might be delivered on Scope, on Cost, and on Schedule, but it resulted in multiple fatalities, had a devastating environmental impact, and ruined the organizational reputa-tion. Concerning fatalities, polluted environment, or devastated reputation, shouldn’t an organization be ready to ask “How much should we pay to com-pensate for occurred environmental, safety, and reputation risks?”5 Or should it rather manage corresponding “soft” objectives and deviations from them

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consistently? The following “soft” objectives are widely used or should be used these days to make risk management more comprehensive:

▪ Safety ▪ Environment ▪ Reputation

The Safety objective will be understood as health and safety (H&S) in this book in most cases.

These soft objectives are normally treated as additional “goal‐zero” types of constraints: no fatalities and injuries, no negative impacts on Environment and Reputation. A longer list of additional constrains could be adopted by a project to also reflect on stakeholders’ management, legal objectives, profit margin goals, access to oil reserves or new contracts, and so on. Those objectives are more often used at the corporate level.

Deviations from these goal‐zero‐type objectives might be also realized as both general uncertainties and uncertain events. It is the same in the case of Scope, Cost, and Schedule objectives—those could become “corporate risks.”

There is an obvious inconsistency in the terminology of modern risk manage-ment. First, the word risk means something unfavorable. However, when risk is used in risk management it covers both upside (favorable) and downside (unfavor-able) deviations from objectives. Second, when the term risk is used this implies some probability of occurrence, even according to the ISO 31000 standard.6 However, general uncertainties have certainty of occurrence. To fully resolve these two inconsistencies we have to presume the following four categories:

1. Downside uncertain events2. Upside uncertain events3. Downside general uncertainties4. Upside general uncertainties

All deviations from project objectives discussed so far are understood as known. They are normally identified and put on a project’s radar screen. We know that they should be part of risk management activities due to one or both dimensions of uncertainties. In other words, their relevance to a project is believed to be fully certain.

The bad news is that some deviations could be overlooked and would not appear on the risk management radar screen at all (at least until they occur). Following the fundamental observations of modern philosopher Donald Rums-feld, we cannot help introducing the unknown–unknown part of his picture of

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Key Objects of Risk (or Uncertainty) Management ◾ 15

the world (see “Unknown Unknowns”). Those stealth types of objects may be called unknown unknowns . We will call them unknown uncertainties .

UNKNOWN UNKNOWNS “There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.”

Donald Rumsfeld

Discussing various types of uncertainties earlier we implicitly assumed that unbiased workers, who have plenty of time and resources, identify, assess, and address risks using ideal risk methods that they fully understand. Unfortunately, project teams usually work under a severe time crunch; they are normally understaffed; workers have different perceptions of possible risks depending on their previous experience and background; and they have vari-ous levels of training and understanding of risk methods. Moreover, some of them could be interested in identifi cation (or non‐identifi cation) of particular risks and particular assessments and addressing. Even more signifi cant, a com-pany might not have adequate risk methods in its toolbox at all.

The various systematic inconsistencies outlined earlier are referred to in risk management as bias . Bias could stem from features of both organizational aspects of risk management and its psychological aspects. The main types of bias will be discussed in Part II. All of them could have an impact on identifi -cation and assessment of general uncertainties and uncertain events through introducing systematic identifi cation and assessment errors. 7 Some of them may even lead to overlooking uncertainties during identifi cation, making them the infamous unknown unknowns. But room for unknown uncertainties could serve as a measure of quality of a project risk management system.

KEY OBJECTS OF RISK (OR UNCERTAINTY) MANAGEMENT: DO WE REALLY KNOW WHAT WE TRY TO MANAGE?

The previous section brought up quite a few possible deviations from project objectives that defi ne overall uncertainty of project outcome. Surprisingly,

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discussion on definitions of terms such as risk, opportunity, threat, chance, pos-sibility, uncertainty, ambiguity, issues, consequences, likelihood, and so on can be found in many modern publications on risk management and professional forums. Implicit links among these terms as well as nuances of their meanings in various languages are still being discovered and fathomed. It seems that all those discussions have a linguistic nature that does not necessarily have a lot to do with the fundamental nature of uncertainty.

Those are all signs of lack of solid structure and logic in risk management as a discipline. Do you think that representatives of more mature disciplines such as mechanical engineering discuss fundamental differences between compressor and pump stations?

It seems to me that having English as a second language is a benefit that justifies ignoring all those nuances. It also seems that project team members and decision makers, even if they are native English‐language speakers, are not very interested in those nuances, either. At the same time a need to apply first principles related to the fundamental nature of uncertainty to clarify all those definitions has been on my mind for a while.

The recent ISO 31000 standard was an attempt to draw the line at these endless and often futile discussions. As a general guideline supposedly applica-ble to any industry, the ISO 31000 standard doesn’t provide and is not expected to provide a toolbox to adequately assess and manage all types of uncertainties that usually give rise to overall uncertainty of project outcome. Some concepts, definitions, and tools that are required for this are either missing or confus-ing. For instance, the standard defines risk as a potential event as well as the effect of uncertainty on objectives that is characterized by consequences and likelihood of occurrence. This is a core definition that I fully support but in the case of uncertain events only. What if there is no event but there is uncertain impact on project objectives? In other words, what if a given (not potential) uncertainty exists only due to deficiency of knowledge about impact on objec-tives, with likelihood of the impact being 100% certain? What if probability of event is uncertain but possible impacts is fully and clearly defined? What would be the classification and role of uncertain events that did occur (issues)? How about various types of biases and unknown uncertainties? Do we need an ISO 310000‐A standard to manage additional uncertainties like this?

This section is devoted to the introduction of a comprehensive set of practi-cal definitions that can be used in modern project risk management regardless of whatever names or tags we attach to those. A key incentive to do this is to come up with a clear‐cut set of basic notions that can be utilized in practice (not in theory) of risk management of capital projects. Hence, they could be

c01.indd 16 7/31/2013 9:34:10 PM

71


used by project teams and decision makers as international risk management lingo. We don’t intend to develop definitions that fit all risk methods, all indus-tries, or all types of (past, current, and future) projects, or that comply with “Risk Management Kremlin’s” requirement. There is no intent to dogmatize risk management of capital projects, either.

Let’s call these definitions uncertainty objects. All of them have been already introduced indirectly in the previous section in a narrative way. They will be meaningful regardless of the linguistic labels we attach to them. We will keep them in our toolbox, not because of labels and nuances related to them, but because of the utility and consistency they provide when waging war against uncertainty of project outcomes. Table 1.2 recaps the discussion of the previ-ous section in a structured way. (The reader could change the labels of the objects to his or her taste or according to his or her native language as soon as their fundamental nature and role are well understood.) The contributions to project cost and schedule reserves mentioned in Table 1.2 are discussed in Chapters 12 and 14.

All new objects are adequately described by combinations of words that contain the word uncertainty, and not the word risk. The term risk plays a rudi-mentary role in Table 1.2. In a way, the term risk becomes irrelevant. (What an achievement given the title of this book!)

We may use a physics analogy describing relations among molecules and atoms to better understand what happened. In place of the traditional object risk (“a molecule”) we have new objects (“atoms”). Those new objects are defined by possibilities of upside or downside deviations in the case of general uncertainties or uncertain events, which could be known (identified by a project team) or stay unknown until they occur. To further follow the physics analogy, we may define three degrees of freedom associated with an uncertainty:

1. Uncertainty of impact (general uncertainty) versus uncertainty of impact and likelihood (uncertain event)

2. Downside (unfavorable) deviation versus upside (favorable) deviation3. Known (identified) uncertainty versus unknown (unidentified) uncertainty

These three degrees of freedom generate eight main uncertainty types as Figure 1.2 implies:

1. General Uncertainty (GU)—Downside (↓)—Known (K) {GU↓K}2. General Uncertainty (GU)—Upside (↑)—Known (K) {GU↑K}

c01.indd 17 7/31/2013 9:34:10 PM

72

18

TAB

LE 1

.2

Key

Unc

erta

inty

Ob

ject

s

Unc

ert

aint

y Ty

pe

Unc

ert

aint

y O

bje

ct

Dev

iati

on

Fro

m

Up

sid

e o

r D

ow

nsi

de?

C

om

me

nts

N/A

Pr

ojec

t B

asel

ines

N

/A

N/A

H

ypot

hetic

al s

et o

f one

‐po

int

valu

es t

hat

are

pro

clai

med

fully

cer

tain

to

rep

rese

nt u

ncer

tain

ty‐f

ree

pro

ject

ob

ject

ives

.

Giv

en

[pro

bab

ility

: ce

rtai

n; im

pac

t:

cert

ain]

Issu

e A

ny

ob

ject

ive

↑↓Is

sues

red

e� n

e b

asel

ines

. Iss

ues

app

ear

whe

n a

gen

eral

unc

erta

inty

bec

om

es

cert

ain

in t

erm

s of

imp

act

or

unce

rtai

n ev

ent

occ

urs

and

bec

om

es c

erta

in

in t

erm

s of

bot

h p

rob

abili

ty a

nd im

pac

t. A

n is

sue

can

be

asso

ciat

ed w

ith

eith

er u

psi

de

or

do

wns

ide

dev

iatio

n d

epen

din

g o

n th

e na

ture

of a

rea

lized

un

cert

aint

y.

Kno

wn

(or

Unk

now

n) G

ener

al

Unc

erta

inty

[p

rob

abili

ty:

cert

ain;

imp

act:

un

cert

ain]

Des

ign

Unc

erta

inty

C

apE

x,

Sco

pe

↓ D

esi

gn

allo

wan

ce is

use

d t

o ad

dre

ss d

esig

n un

cert

aint

y. N

orm

ally

it is

not

p

art

of r

isk

man

agem

ent

alth

oug

h sh

oul

d b

e ke

pt

in m

ind

whe

n as

sess

ing

the

ot

her

ob

ject

s.

Gen

eral

Co

st

Unc

erta

inty

C

apE

x

↑↓

Ap

plic

able

to

each

est

imat

e’s

cost

acc

oun

t. C

ont

rib

ute

to p

roje

ct c

ost

co

ntin

ge

ncy .

Gen

eral

D

urat

ion

Unc

erta

inty

Sche

dul

e A

pp

licab

le t

o ea

ch n

orm

al a

ctiv

ity.

Co

ntri

but

e to

pro

ject

sch

ed

ule

rese

rve .

Co

st

Esc

alat

ion

Cap

Ex

Take

n in

to a

cco

unt

thro

ugh

esca

lati

on

rese

rve ;

in c

ase

of d

e‐es

cala

tion

coul

d b

e us

ed fo

r se

lect

ion

of p

urch

asin

g t

ime.

Cur

renc

y E

xcha

nge

Rate

U

ncer

tain

ty

Cap

Ex

Take

n in

to a

cco

unt

thro

ugh

exch

ang

e ra

te r

ese

rve .

Co

uld

be

avo

ided

/tr

ansf

erre

d t

hro

ugh

hed

gin

g.

c01.indd 18 7/31/2013 9:34:11 PM

73

19

Sc

hed

ule

Dri

ven

Co

sts

Cap

Ex

Dis

trib

utio

n of

co

mp

letio

n d

ates

and

ass

oci

ated

ran

ge

of s

ched

ule

del

ays

conv

erte

d t

o ex

tra

cost

s; t

aken

into

acc

oun

t th

roug

h ap

plic

atio

n of

bur

n ra

tes

in in

teg

rate

d p

rob

abili

stic

co

st a

nd s

ched

ule

risk

mo

del

s as

a c

ost

gen

eral

un

cert

aint

y an

d g

ive

rise

to

pro

ject

co

st r

ese

rve .

Bur

n ra

tes

coul

d b

e co

nsid

ered

aux

iliar

y g

ener

al u

ncer

tain

ties.

O

rgan

izat

iona

l B

ias

Any

o

bje

ctiv

e Sy

stem

atic

err

ors

in id

enti

� cat

ion

and

ass

essm

ent

of a

ll p

roje

ct

unce

rtai

ntie

s. D

ue t

o hu

man

nat

ure

and

bus

ines

s re

alit

ies,

bia

s p

erta

ins

to a

ll p

roje

ct t

eam

s to

a c

erta

in d

egre

e as

a g

ener

al u

ncer

tain

ty. I

n so

me

case

s m

ay le

ad t

o up

sid

e d

evia

tio

ns f

rom

pro

ject

ob

ject

ives

. Var

ious

an

ti‐b

ias

and

cal

ibra

tio

n m

etho

ds

sho

uld

be

in p

lace

to

sup

pre

ss t

hese

sy

stem

atic

err

ors

.

Su

bco

nsci

ous

B

ias

Any

o

bje

ctiv

e

C

ons

cio

us B

ias

Any

o

bje

ctiv

e

Dis

cret

e U

ncer

tain

Eve

nt

[pro

bab

ility

: un

cert

ain;

imp

act:

ce

rtai

n]

Dis

cret

e U

ncer

tain

Ev

ent

Any

o

bje

ctiv

e ↑↓

(Kno

wn

or

unkn

ow

n) u

ncer

tain

eve

nts

wit

h cl

earl

y p

red

icta

ble

one

‐po

int

imp

acts

on

ob

ject

ives

co

uld

be

sing

led

out

as

dis

cret

e un

cert

ain

even

ts.

Kno

wn

dis

cret

e un

cert

ain

even

ts o

f co

st im

pac

ts c

ont

rib

ute

to p

roje

ct c

ost

ri

sk r

ese

rve

alo

ng w

ith

unce

rtai

n ev

ents

.

Dow

nsid

e U

ncer

tain

Ev

ent

Any

o

bje

ctiv

e ↓

Tho

se t

wo

cate

go

ries

are

tra

diti

ona

l sub

ject

s of

ris

k m

anag

emen

t th

at

are

calle

d r

isks

or

sep

arat

ely

thre

ats

and

op

po

rtun

ities

in r

isk

jarg

on.

K

now

n un

cert

ain

even

ts o

f co

st im

pac

ts g

ive

rise

to

pro

ject

co

st

risk

re

serv

e.

U

psi

de

Unc

erta

in

Even

ts

Any

o

bje

ctiv

e ↑

(Co

ntin

ued

)

c01.indd 19 7/31/2013 9:34:11 PM

74

20

Unc

ert

aint

y Ty

pe

Unc

ert

aint

y O

bje

ct

Dev

iati

on

Fro

m

Up

sid

e o

r D

ow

nsi

de?

C

om

me

nts

Kno

wn

Unc

erta

in

Even

t [p

rob

abili

ty:

unce

rtai

n; im

pac

t:

unce

rtai

n]

Una

ccep

tab

le

Perf

orm

ance

an

d L

Ds

Cap

Ex,

Sc

op

e,

Qua

lity/

Perf

orm

ance

, Re

put

atio

n

↓ Th

ese

coul

d b

e st

and

alo

ne d

ow

nsid

e un

cert

ain

even

ts d

epen

din

g o

n co

rpo

rate

� na

ncia

l rep

ort

ing

. If Q

ualit

y / Pe

rfo

rman

ce o

bje

ctiv

e is

not

met

up

on

pro

ject

co

mp

letio

n, p

erf

orm

ance

allo

wan

ce w

oul

d b

e us

ed t

o ad

dre

ss

po

or

per

form

ance

(per

form

ance

war

rant

y). I

n ca

se s

om

e cl

ause

s st

ipul

ated

b

y a

pro

ject

co

ntra

ct (c

ons

eque

ntia

l dam

ages

, sch

edul

e d

elay

s, t

urno

ver

of

key

per

sonn

el, e

tc.)

are

not

ob

eyed

, liq

uid

ate

d d

amag

es

may

be

incu

rred

.

Kno

wn

Show

‐St

op

per

/Gam

e C

hang

er

Any

o

bje

ctiv

e ↓

Pro

bab

ility

of o

ccur

renc

e is

usu

ally

ver

y lo

w a

nd im

pac

ts a

re d

evas

tatin

g

that

des

troy

(sho

w‐s

top

per

: kno

cko

ut im

pac

t) o

r d

rast

ical

ly r

ede�

ne

(gam

e ch

ang

er: k

nock

do

wn

imp

act)

bas

elin

es. C

ons

ider

ed p

art

of c

orp

ora

te r

isk

man

agem

ent

and

not

incl

uded

in p

roje

ct r

eser

ves.

Unk

now

n U

ncer

tain

Eve

nt

[exi

sten

ce:

unce

rtai

n]

Unk

now

n D

owns

ide

Unc

erta

in

Even

t

Any

o

bje

ctiv

e ↓

Stay

s un

iden

ti� e

d u

ntil

occ

urs;

new

tec

hno

log

y an

d g

eog

rap

hy a

s w

ell a

s va

rio

us t

ypes

of b

ias

are

maj

or

sour

ces.

Als

o p

roje

ct c

hang

es (b

asel

ine’

s re

de�

niti

on)

in c

ase

chan

ges

are

not

ad

equa

tely

man

aged

co

uld

be

a so

urce

. M

ay b

e co

vere

d b

y a

spec

ial c

ost

or

sche

dul

e u

nkn

ow

n–u

nkn

ow

n re

serv

e (a

llow

ance

) .

Unk

now

n U

psi

de

Unc

erta

in

Even

t

Any

o

bje

ctiv

e ↑

Stay

s un

iden

ti� e

d u

ntil

occ

urs;

new

tec

hno

log

y an

d g

eog

rap

hy a

s w

ell a

s va

rio

us t

ypes

of b

ias

are

maj

or

sour

ces.

Unk

now

n Sh

ow

‐Sto

pp

er/

Gam

e C

hang

er

Any

o

bje

ctiv

e ↓

Bei

ng t

ype

of u

nkno

wn,

sta

ys u

nid

enti�

ed

unt

il o

ccur

s; n

ew t

echn

olo

gy

and

geo

gra

phy

as

wel

l as

vari

ous

typ

es o

f bia

s ar

e m

ajo

r so

urce

s. A

lso

pro

ject

cha

nges

(bas

elin

e’s

red

e� n

itio

n) in

cas

e ch

ang

es a

re n

ot a

deq

uate

ly

man

aged

co

uld

be

a so

urce

. Pro

bab

ility

of o

ccur

renc

e is

usu

ally

ver

y lo

w

and

imp

acts

are

dev

asta

ting

tha

t d

estr

oy (s

how

‐sto

pp

er: k

nock

out

imp

act)

o

r d

rast

ical

ly r

ede�

ne

(gam

e ch

ang

er: k

nock

do

wn

imp

act)

bas

elin

es.

Co

nsid

ered

par

t of

co

rpo

rate

ris

k m

anag

emen

t.

TAB

LE 1

.2

(Co

ntin

ued

)

c01.indd 20 7/31/2013 9:34:12 PM

75


3. General Uncertainty (GU)—Downside (↓)—Unknown (U) {GU↓U} 4. General Uncertainty (GU)—Upside (↑)—Unknown (U) {GU↑U} 5. Uncertain Event (UE)—Downside (↓)—Known {UE↓K} 6. Uncertain Event (UE)—Upside (↑)—Known {UE↑K} 7. Uncertain Event (UE)—Downside (↓)—Unknown {UE↓U} 8. Uncertain Event (UE)—Upside (↑)—Unknown {UE↑U}

Moving from molecules to atoms represented a natural path of science when accumulated knowledge allowed one to better fathom objects of Nature and describe them more adequately and in more detail. The same thing hap-pens when we better understand what we used to call “risk.”

One may wonder about the placement of some additional or missing objects such as issues and discrete uncertain events in Figure 1.2 . Those were dis-cussed in the previous section and mentioned in Table 1.2 . We might make another step “from atoms to electrons, protons, and neutrons” on the way to higher complexity and better understanding. This should double the size of the cube in Figure 1.2 . As a result, in place of two categories describing probabilities and impacts we should get four (see Figure 1.3 ):

1. Issue (probability: certain; impact: certain) 2. General uncertainty (probability: certain; impact: uncertain) 3. Discrete uncertain event (probability: uncertain; impact: certain) 4. Uncertain event (probability: uncertain; impact: uncertain)

FIGURE 1.2 Three Uncertainty Degrees of Freedom

Upside Deviation (↑)

Downside Deviation (↓)

General Uncertainty (GU)

Uncertain Event (UE)Known Uncertainty (K)

Unknown Uncertainty (U)

c01.indd 21 7/31/2013 9:34:12 PM

76


The addition of extra objects generates a bit too much complexity, which could be overshooting the purpose of this book. Let’s keep increasing the level of complexity to academic studies and books. To keep things simple, let’s treat an issue as limiting realization of a general uncertainty when impact uncer-tainty vanishes. Similarly, a discrete uncertain event should be understood as limiting realization of an uncertain event when the possible impact is fully cer-tain. This convention should allow one to avoid adding extra objects to Figure 1.2 , which is informative enough. At the same time, all major objects of risk management are comprehensively defi ned from fi rst principles by Figures 1.2 and 1.3 . Moreover, the arrows in Figure 1.3 represent possible transformations among discussed objects in the course of project development and execution.

To be consistent let’s summarize this discussion through formal introduc-tion of four degrees of freedom of uncertainties as follows:

1. Probability: certain (100%) versus uncertain (< 100%) 2. Impact: certain (one‐point) versus uncertain (“range”) 3. Favorability: upside (favorable) versus downside (unfavorable) 4. Identifi cation: known (identifi ed) versus unknown (unidentifi ed)

FIGURE 1.3 Uncertainty versus Certainty of Impacts and Likelihoods FIGURE 1.3 Uncertainty versus Certainty of Impacts and Likelihoods

General Uncertainty:Range of impacts vs. probability 100%

Uncertain Event:Range of impacts vs. probability <100%

Issue:One-point certain impacts vs.

probability 100%

Discrete Uncertain Event:One-point certain impacts vs.

probability <100%

No Game of Chance (probability 100%)

Cer

tain

Imp

act

Un

cert

ain

Imp

act

Game of Chance (probability <100%)

c01.indd 22 7/31/2013 9:34:12 PM

77


These four academic uncertainty degrees of freedom (introduced for consis-tency) will not be used in this book. We will ignore them and will use practi-cal uncertainty objects generated by those degrees described by Table 1.2 and Figures 1.2 and 1.3.

I’m sorry for using an approach that looks more and more like quantum physics. For readers who don’t appreciate analogies from science we may turn to a linguistic analogy such as associating the English language with England. Due to the enormous popularity and success of the English language all over the world in the past few decades and the existence of a number of dialects, accents, and versions, the English language is not associated just with England anymore, as it was in the times of Shakespeare.8 To me, it’s about the United States or Canada these days, despite the fact that I did go to business school in England. For some people it could be about Australia or India, South Africa or Zimbabwe. Even the highly successful 2012 Summer Olympic Games that were hosted in London, England, won’t change this much. So, geographically we may distinguish English English, American English, Canadian English, Australian English, East Indian English, and so on, not to mention the multiple versions of English used in the rest of the United Kingdom as well as Spanglish, Chinglish, or Russglish, which I speak fluently.

Should we not treat and interpret words such as risk management and risk in a similar way? The word risk sounds like a linguistic analogy to English, and risk management to English English. I feel that more appropriate and comprehensive would be the words uncertainty and uncertainty management, which reflect much better the spectrum of objects required to handle overall uncertainty of proj-ect outcomes. In light of the more precise and clear definitions of uncertainty objects introduced by Table 1.2 and Figures 1.2 and 1.3, the word risk sounds more like a vague piece of jargon that could mean everything and nothing.

Should risk analysts, coordinators, managers, and subject matter experts (SMEs) agitated by these speculations rush in with proposals to management to change their job titles accordingly? Probably not (yet). We should not break with traditions so easily even when they no longer reflect reality. We should cherish them even without any visible reason. I will keep my current good old title of Director, Risk Management, intact. Moreover, I would not support such proposals from my co‐workers even if I do understand them. Once again, it’s not about labels or titles. So let’s keep it calling “risk management,” meaning “uncertainty management.”

Although I tend to use traditional words and phrases such as risk, risk register, risk management, and risk management plan, all those r‐words should be understood as u‐words in all cases. Another main reason to continue using the

c01.indd 23 7/31/2013 9:34:12 PM

78


word risk every now and then in place of uncertainty is that it is conveniently short, containing only four letters and one syllable.

UNCERTAINTY EXPOSURE CHANGERS

Table 1.2 presents key uncertainty objects that are understood as static and that outline a snapshot of overall project uncertainty exposure in a given moment. What is missing in this picture is time and uncertainty dynamics. So, if you thought that the four uncertainty degrees of freedom are enough, you would be wrong. The fi fth degree of freedom is time. As time actually introduces changes or dynamics of project uncertainties objects, in place of that additional degree (time) we will use its representative objects, as follows.

Overall project uncertainty exposure is volatile and depends on a lot of ongoing changes and activities in a project’s internal and external environ-ment. Let’s call them uncertainty exposure changers or just changers . They may be external and internal to a project, but they also may be controllable and uncontrollable by a project team.

External uncertainty exposure changers include any dynamics or trans-formations of givens and facts that are causes of uncertainties relevant to a project. For instance, changes in tax or environmental regulations could be introduced as external uncertainty changers.

Internal uncertainty exposure changers include any decisions and choices relevant to a project done by a project team. Amendments of project‐related assumptions are also qualifi ed for this category. These changers infl uence dynamics and transformation of causes of uncertainties relevant to a project. Decisions, choices, and amended assumptions should not be considered risk management controls since they are usually aimed at shaping project objec-tives and baselines.

Uncertainty addressing actions make up a special group of internal uncertainty changers. As discussed in Chapter 5 , there are two major types of addressing actions: preventive and recovery. Uncertainty addressing actions should be considered major risk management controls to amend project uncer-tainty exposure in a focused way.

Another angle from which to view changers is the degree of infl uence a project team has over them. In other words, can a project team guarantee that a changer leads to expected and predictable results planned by the project team for certain? If the answer is somewhat uncertain, this could be considered uncontrollable. For example, implementation of a decision may depend on an approval or a commitment by third parties or stakeholders. Even if an approval

c01.indd 24 7/31/2013 9:34:12 PM

79

Uncertainty Exposure Changers ◾ 25

is expected from top management of the same organization, this introduces an uncertainty aspect to a project, anyway. For example, a project team might ask management about early procurement of long lead items prior to a fi nal investment decision. Even if a project team builds a strong case to support this, the fi nal decision is uncertain and depends on management. As a result, the decision should be regarded as an upside uncertain event (or opportunity in risk jargon) with some probability of happening.

Similarly, any uncertainty addressing action could fully or partially fail. Potential of failure is reciprocal to the control a project team has over imple-mentation of the action.

Volatility of external uncertainty changers is comparable to volatility of the stock markets as this includes volatility of the general economic situa-tion and activities of multiple project stakeholders. It is unlikely that a project team would have much control over external uncertainty changers. The only method to infl uence them somehow relates to implementation of uncertainty addressing actions (internal changers). Obviously, such addressing actions do not often lead to full control of external changers. For instance, a project team may try to build relations with external stakeholders (e.g., local communities) in order to reduce or avoid a risk of opposition to the project. In some very rare cases this might lead to full control of the external stakeholders’ intentions that allows them to fully avoid the risk of opposition.

FIGURE 1.4 Main Types of Project Uncertainty Changers

External Uncontrollable UncertaintyChangers:

Transformation of facts, givens, etc.in external environment (causes

of uncertainties) withoutfull control by a project team

External Controllable UncertaintyChangers:

Transformation of facts, givens, etc.in external environment

(causes of uncertainties) under fullcontrol by a project team

Internal Uncontrollable UncertaintyChangers:

Decisions, choices, amended assumptions,etc. (causes of uncertainties) and

uncertainty addressing actionsnot fully controllable by a project team

Internal Controllable UncertaintyChangers:

Decisions, choices, amended assumptions,etc. (causes of uncertainties) and

uncertainty addressing actionsfully controllable by a project team

Controllable (Certain) Uncontrollable (Uncertain)

Ext

ern

alIn

tern

al

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The bottom line is that uncertainty changers could be external and inter-nal and wage a tug of war with each other. They could be either controllable/certain or uncontrollable/uncertain (see Figure 1.4 ). This approach is sup-ported by a main uncertainty identifi cation tool (bowtie diagram) discussed in Chapter 4 . The bowtie diagram includes causes of uncertainties, addressing actions, and risk breakdown structure (RBS) describing the external and inter-nal project environment. In addition, this discussion leads to the important topic of proper assessment of uncertainties after addressing (Chapter 5 ) due to the possibility of an action’s failure.

CONCLUSION

This chapter links overall uncertainty of a project outcome with all major con-tributing uncertainty factors (objects) that give rise to this. The degrees of free-dom of uncertainties were introduced to explore and generate a rich spectrum of uncertainty objects.

Dynamics of uncertainty objects was introduced through internal and external changers. These could be either controllable (certain) or uncontrol-lable (uncertain).

As soon as all major objects of project uncertainty are revealed and the main types of uncertainty changers are singled out, focused selection of ade-quate methods to handle uncertainty objects should commence. There is no silver bullet that allows control of all uncertainties in a consistently effi cient way. A tailor‐made approach is required to match challenges with methods. The number of adequate and crucial methods to handle all types of uncertain-ties is quite small. The rest of the book is devoted to a detailed overview of the limited number of the most effi cient and adequate methods that zero in on particular types of uncertainties and their changers.

NOTES

1. IPA Institute, “Successful Mega Projects” Seminar (Calgary, Alberta, Canada 2009), p.18.

2. A. Dubi, Monte Carlo Applications in System Engineering (Hoboken, NJ: John Wiley & Sons, 2000).

3. C. Ebeling, An Introduction to Reliability and Maintainability Engineering (Long Grove, IL: Waveland Press, 1997).

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Notes ◾ 27

4. C. Chapman and S. Ward, Project Risk Management: Processes, Techniques and Insights (Chichester, England: John Wiley & Sons, 2003).

5. One European organization recently “found an answer” to this question as a result of an infamous incident in the Gulf of Mexico. The price tag is several billion dollars in legal damages and counting; environment and company reputation are severely damaged; several people are dead. No doubt, it is more reasonable to manage risks of safety, environment and reputation impacts before they happen (preventive approach) than pay a huge price (and not only in monetary terms) after they occur (crisis management).

6. ISO 31000 International Standard: Risk Management: Principles and Guidelines (Switzerland: International Organization for Standardization, 2009).

7. D. Hubbard, The Failure of Risk Management: Why It’s Broken and How to Fix It (Hoboken, NJ: John Wiley & Sons, 2009).

8. R. McCrum, W. Cran, and R. MacNeil, The Story of English (London: Faber & Faber, 2011).

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Operational Risk ManagementA Complete Guide to a Successful Operational Risk FrameworkPhilippa X. Girling978-1-118-53245-4 • Hardback • 352 pages • November 2013

Buy Now!


£65.00 £39.00 / €76.00 €45.60 / $95.00 $57.00


83

1

Chapter 1Definition and Drivers of

Operational risk

this chapter examines the definition of operational risk and its formal adoption in Basel II. The requirements to identify, assess, control, and

mitigate operational risk are introduced, along with the four causes of op-erational risk—people, process, systems, and external events—and the seven risk types. The definition is tested against the 2012 London Olympics. The different roles of operational risk management and measurement are intro-duced, as well as the role of operational risk in an enterprise risk manage-ment framework.

the DefinitiOn Of OperatiOnal risk

What do we mean by operational risk?Operational risk management had been defined in the past as all risk

that is not captured in market and credit risk management programs. Early operational risk programs, therefore, took the view that if it was not market risk, and it was not credit risk, then it must be operational risk. However, today a more concrete definition has been established, and the most com-monly used of the definitions can be found in the Basel II regulations. The Basel II definition of operational risk is:

. . . the risk of loss resulting from inadequate or failed processes, people and systems or from external events.

This definition includes legal risk, but excludes strategic and reputational risk.1

Let us break this definition down into its components. First, there must be a risk of loss. So for an operational risk to exist there must be an

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2 OperatiOnal risk ManageMent

associated loss anticipated. The definition of “loss” will be considered more fully when we look at internal loss data in Chapter 7, but for now we will simply assume that this means a financial loss.

Next, let us look at the defined causes of this loss. The preceding definition provides four causes that might give rise to operational risk losses. These four causes are (1) inadequate or failed processes, (2) inadequate or failed people (the regulators do not get top marks for their grammar, but we know what they are getting at), (3) inadequate or failed systems, or (4) external events.

While the language is a little awkward (what exactly are “failed people,” for example), the meaning is clear. There are four main causes of operational risk events: the person doing the activity makes an error, the process that supports the activity is flawed, the system that facilitated the activity is bro-ken, or an external event occurs that disrupts the activity.

With this definition in our hands, we can simply look at today’s news-paper or at the latest online headlines to find a good sample of operational risk events. Failed processes, inadequate people, broken systems, and violent external events are the mainstay of the news. Operational risk surrounds us in our day‐to‐day life.

Examples of operational risk in the headlines in the past few years in-clude egregious fraud (Madoff, Stanford), breathtaking unauthorized trad-ing (Société Générale and UBS), shameless insider trading (Raj Rajaratnam, Nomura, SAC Capital), stunning technological failings (Knight Capital, Nasdaq Facebook IPO, anonymous cyber‐attacks), and heartbreaking ex-ternal events (hurricanes, tsunamis, earthquakes, terrorist attacks). We will take a deeper look at several of these cases throughout the book.

All of these events cost firms hundreds of millions, and often billions, of dollars. In addition to these headline‐grabbing large operational risk events, firms constantly bleed money due to frequent and less severe events. Broken processes and poorly trained staff can result in many small errors that add up to serious downward pressure on the profits of a firm.

The importance of these types of risks, both to the robustness of a firm and to the systemic soundness of the industry, has led regulators to push for strong operational risk frameworks, and has driven executive managers to fund and support such frameworks.

The Basel II definition of operational risk has been adopted or adapted by many firms and is now generally accepted as the standard. It has been incor-porated into national regulations across the globe with only minor adaptations and is consistently referred to by regulators and operational risk managers.

Basel II is the common name used to refer to the “International Convergence of Capital Measurement and Capital Standards: A Revised Framework,” which was published by the Bank for International Settlements in Europe in 2004.

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Definition and Drivers of Operational Risk 3

The Basel II framework set out new risk rules for internationally active financial institutions that wished to continue to do business in Europe. These rules related to the management and capital measurement of market and credit risk, and introduced a new capital requirement for operational risk. In addition to the capital requirement for operational risk, Basel II laid out qualitative requirements for operational risk man-agement, and so a new era of operational risk management development was born.

JPMorgan Chase has adapted the definition very simply as follows:

Operational risk is the risk of loss resulting from inadequate or failed processes or systems, human factors or external events.2

Deutsche Bank has a more creative interpretation:

Operational risk is the potential for failure (incl. the legal com-ponent) in relation to employees, contractual specifications and documentation, technology, infrastructure and disasters, external influences and customer relationships.

Operational risk excludes business and reputational risk.3

Under the Basel II definition, legal events are specifically included in the definition of operational risk, and a footnote is added to further clarify this.

Legal risk includes, but is not limited to, exposure to fines, penal-ties, or punitive damages resulting from supervisory actions, as well as private settlements.4

This is a helpful clarification, as there is often some tension with the legal department when the operational risk function first requests informa-tion on legally related events. This is something that will be considered in more detail later in the section on loss data collection.

The Basel II definition also specifically excludes several items from operational risk:

This definition includes legal risk, but excludes strategic and repu-tational risk.5

These nuances in the Basel II definition are often reflected in the defini-tion adopted by a firm, whether or not they are governed by that regulation. However, these exclusions are not always applied in operational risk frameworks.

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For example, some firms have adopted definitions of operational risk that include reputational risk. For example, Citi’s definition includes repu-tational risk:

Operational risk is the risk of loss resulting from inadequate or failed internal processes, systems or human factors, or from exter-nal events. It includes the reputation and franchise risk associated with business practices or market conduct in which Citi is involved.6

We will be looking at ways that operational risk management and mea-surement can meet the underlying need to accomplish five tasks:

1. Identifying operational risks. 2. Assessing the size of operational risks. 3. Monitoring and controlling operational risks. 4. Mitigating operational risks. 5. Calculating capital to protect you from operational risk losses.

These five requirements occur again and again in global and national regulations and are the bedrock of successful operational risk management.

In addition to putting these tools in place, a robust operational risk framework must look at all types of operational risk. There are seven main categories of operational risk as defined by Basel II.

Before we dive into how operational risk impacts the financial services industry, let’s take a step back and see how other business have been ad-dressing operational risk.

The 2012 Summer Olympics and Paralympics in London, England, pro-vide an interesting case study in how operational risk is managed outside financial services and a practical view into how the basic elements of opera-tional risk management have been applied.

2012 lOnDOn OlympiCs: a Case stuDy7

At the end of the summer of 2012 the Paralympic flame was extinguished in London, bringing the Summer Olympics and Paralympics to a triumphant close. By all accounts both Games were a resounding success, and there has been much proud puffing of British chests and declaring of “Happy and Glorious!”

Before the opening ceremony, London mayor Boris Johnson had ad-mitted that there would be “imperfections and things going wrong” as the capital coped with the Olympics.8

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However, at the opening ceremony, London 2012 Olympic Chairman Lord Sebastian Coe confidently declared: “One day we will tell our children and our grandchildren that when our time came we did it right.”9

It is unlikely that Lord Coe and his team turned to banking regulations to assist them in this task, but the Games do offer us an interesting oppor-tunity to assess whether the Basel II operational risk requirements stand up to a “real world” test. Is Lord Coe an excellent operational risk manager? Will we see him as a headline speaker at a future risk conference? (Spoiler alert: He has my vote.)

The Basel requirements are designed to ensure that there is an adequate framework in place to manage any risks resulting from failed or inadequate processes, people, and systems or from external events. These were exactly the risks that faced the London 2012 team as they prepared to unleash a global event on the crowded city of London. The four main causes of opera-tional risk were there in abundance.

People: Nervous athletes, opinionated officials, aggressive press, ter-rorists, disgruntled Londoners, (missing) security guards, confused volunteers, crazed fans, lost children, heads of state, visiting digni-taries, and the list goes on.

Processes and systems: Stadium building and preparation, ticket sales, transportation, opening ceremonies, closing ceremonies, Olympic village management, cleaning, feeding, running races, organizing matches, safety checks of the parallel bars, awarding medals, play-ing anthems, global broadcasting, keeping that darned flame alight, and the list goes on.

External events: Two words—London weather.

In the most recent Bank of International Settlements Sound Practices document the rules require risk management activities that identify and as-sess, monitor and report, and control and mitigate operational risks. Was this how Lord Coe pulled it off? Did he ensure that the London 2012 team excelled in all of those practices?

The Basel rules also provide seven categories of risk for us to fit any operational risk events into.10 The risk categories certainly seem compre-hensive to those of us in the banking industry, but do they truly capture all operational risks? The categories we are given to work with are:

■ Internal Fraud: Losses due to acts of a type intended to defraud, mis-appropriate property or circumvent regulations, the law, or company policy, excluding diversity/discrimination events, which involves at least one internal party.

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■ External Fraud: Losses due to acts of a type intended to defraud, misap-propriate property, or circumvent the law, by a third party.

■ Employment Practices and Workplace Safety: Losses arising from acts inconsistent with employment, health, or safety laws or agreements; from payment of personal injury claims; or from diversity/discrimination events.

■ Clients, Products, and Business Practices: Losses arising from an unin-tentional or negligent failure to meet a professional obligation to specific clients (including fiduciary and suitability requirements), or from the nature or design of a product.

■ Damage to Physical Assets: Losses arising from loss or damage to physi-cal assets from natural disaster or other events.

■ Business Disruption and System Failures: Losses arising from disruption of business or system failures.

■ Execution, Delivery, and Process Management: Losses from failed trans-action processing or process management, from relations with trade counterparties and vendors.

We will learn more about these categories later, but first we will test them out in the real world.

test One: Do the seven Basel Operational risk Categories Work in the real World?

Let’s take a look at the categories and see if they match up with those salacious Olympics headlines that popped up over the summer:

■ Internal Fraud: “Olympic Badminton Players Disqualified for Trying to Lose”11

■ External Fraud: “London Olympics Fake Tickets Create ‘Honeypot’ for Criminals”12

■ Clients, Products, and Business Practices: “Empty Seats at Olympic Venues Prompt Investigation”13

■ Employment Practice and Workplace Safety: “Dispute Between London Olympics and Musicians Union Heats Up”14

■ Execution, Delivery, and Process Management: “NATB Calls London Olympics Ticket Distribution a Failure”15

■ Damage to Physical Assets: “Olympic Security Shortfall Called ‘Absolute Chaos’”16

■ Business Disruption and System Failure: “London 2012: Traffic Jams and Impact of Games Lanes”17

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Certainly, the Olympics raised risks in each of the categories. Indeed, over eight years of working in operational risk with clients ranging from banks to commodities shipping firms and from law firms to tourism and hospitality conglomerates, I have found the Basel seven categories have proven remarkably resilient and comprehensive.

test two: the risk management tools

Managing the Olympic Games and Paralympic Games was without doubt an enormous challenge in operational risk management. So the next test, and surely the more important one, is whether the recent Sound Practices requirements cover the bases? (Note: We will not be discussing why baseball is not an Olympic sport).

Risks did materialize, and the headlines were at times brutal, but the final wrap‐up headlines were consistently positive. Did the London 2012 team avert disaster by applying the tenets of good operational risk management? Did they identify and assess, monitor and report, and control and mitigate the risks?

Yes, they did. In the Annual Report of the London Organising Committee of the Olympic Games and Paralympic Games Ltd. (LOCOG),18 the team outline the “principal risks and uncertainties” that they face and describe their methodology for managing these risks as follows:

Management use a common model to identify and assess the impact of risks to their business. For each risk, the likelihood and consequence are identified, management controls and the frequency of monitoring are confirmed and results reported. (emphasis added, p. 33)

To be a stickler for accuracy, I will concede that the word mitiga-tion is referenced only for budget risks and security risks, but it is clear in the report that mitigation of the risks identified was the key purpose of the risk management activities. In addition, according to their own website,19 the London Prepares series, the official London 2012 sports testing program, helped to test vital areas of operations ahead of the London 2012 Games.

The Basel rules were first published in 2004 and have not changed fun-damentally since that time. It is interesting, and somewhat comforting, to see that the language of operational risk management has become remarkably consistent—the same risk categories and the same tenets of best practices apply whether you are a bank or an Olympic Games.

London Mayor Boris Johnson admitted that there would be “imperfec-tions and things going wrong”20 as the capital coped with the Olympics.

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For the record, I like this as a new definition for operational risk. Operational risk management does not ensure that nothing will go wrong, but instead focuses on identifying and assessing what can go wrong, on monitoring and reporting changes in risk, and mitigating and controlling the impact of any events that are threatening to occur, or that have occurred and need speedy and effective cleanup.

It’s real‐world risk management, and that is why operational risk man-agers get so passionate about their discipline. Operational risk exists in every industry and in every endeavor. It exists in massive global multimedia extravaganzas and in small local events. It does appear that the Basel opera-tional risk management rules are applicable across the board. Job well done, Bank for International Settlements.

Now whether we need to have all of these rules and also hold bucket loads of capital in case something happens anyway—well, that’s a different discussion for a different chapter (Chapter 12, “Capital Modeling”).

For now, we can agree that an excellent motto for an operational risk de-partment would be Lord Coe’s confident declaration that “one day we will tell our children and our grandchildren that when our time came we did it right.”21

Operational risk has some similarities to market and credit risk. Most im-portant, it should be actively managed because failure to do so can result in a misstatement of an institution’s risk profile and expose it to significant losses.

However, operational risk has some fundamental differences to market and credit risk. Operational risk, unlike market and credit risk, is typically not directly taken in return for an expected reward. Market risk arises when a firm decides to take on certain products or activities. Credit risk arises when a firm decides to do business with a particular counterparty. In con-trast, operational risk exists in the natural course of corporate activity. As soon as a firm has a single employee, a single computer system, a single of-fice, or a single process, operational risk arises.

While operational risk is not taken on voluntarily, the level of that risk can certainly be impacted by business decisions. Operational risk is inherent in any enterprise, but strong operational risk management and measure-ment allows for that risk to be understood and either mitigated or accepted.

OperatiOnal risk management anD OperatiOnal risk measurement

There are two sides to operational risk: operational risk management and oper-ational risk measurement. There is often tension between these two activities, as well as overlap. Basel II requires capital to be held for operational risk and offers several possible calculation methods for that capital, which will be discussed

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later in this chapter. This capital requirement is the heart of the operational risk measurement activities and requires quantitative approaches.

In contrast, firms must also demonstrate that they are effectively man-aging their operational risk, and this requires qualitative approaches. A successful operational risk program combines qualitative and quantitative approaches to ensure that operational risk is both appropriately measured and effectively managed.

Operational risk management

Helpful guidelines for appropriate operational risk management activities in a firm can be found in Pillar 2 of Basel II:

736. Operational risk: The Committee believes that similar rigour should be applied to the management of operational risk, as is done for the management of other significant banking risks. …

737. A bank should develop a framework for managing opera-tional risk and evaluate the adequacy of capital given this framework. The framework should cover the bank’s appetite and tolerance for operational risk, as specified through the policies for managing this risk, including the extent and manner in which operational risk is transferred outside the bank. It should also include policies outlin-ing the bank’s approach to identifying, assessing, monitoring and controlling/mitigating the risk.22

There are several important things to note in these sections. First, opera-tional risk should be managed with the same rigor as market and credit risk. This is an important concept that has many implications when considering how to embed an operational risk management culture in a firm, as will be explored later in this chapter.

Second, policies regarding risk appetite are required. This is no easy task, as articulating a risk appetite for operational risk can be very challenging. Most firms would prefer to have no operational risk, and yet these risks are inherent in their day‐to‐day activities and cannot be completely avoided. Recently, regulators have been very interested in how firms are responding to this challenge, and there is much debate about how to express opera-tional risk appetite or tolerance and how to manage against it. This will be explored further in each of the framework sections later in the chapter.

Finally, policies must be written that outline the bank’s approach to “identifying, assessing, monitoring, and controlling/mitigating” operational risk. This is the heart of the definition of operational risk management, and the elements of an operational risk framework need to address these

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challenges. Does each element contribute to the identifi cation of operational risks, the assessment of those risks, the monitoring of those risks, and the control or mitigation of those risks? To be successful, an operational risk framework must be designed to meet these four criteria for all operational risk exposures, and it takes a toolbox of activities to achieve this.

In the operational risk management toolbox are loss data collection programs, risk and control self‐assessments, scenario analysis activities, key risk indicators, and powerful reporting. (See www.wiley.com/go/girling for access to sample toolbox templates.) Each of these elements will be consid-ered in turn in this book.

Operational risk measurement

Operational risk measurement focuses on the calculation of capital for operational risk, and Basel II provides for three possible methods for cal-culating operational risk capital, which will be discussed later. Some fi rms choose to calculate operational risk capital, even if they are not subject to a regulatory requirement, as they wish to include the operational risk capital in their strategic planning and capital allocation for strategic and business reasons.

the relationship between Operational risk management and Other risk types

Operational risk often arises in the presence of other risk types, and the size of an operational risk event may be dramatically impacted by market or credit risk forces.

eXample

One of Gamma Bank’s business lines offers retail customers the ability to trade bonds. One of the customers calls the broker at Gamma Bank and instructs the broker to buy Andromeda Corporation bonds for the customer’s account. The trade is executed, but it is mistakenly booked as a sell, instead of a buy; this will result in a signifi cantly larger loss if the market moves up.

The cost of making the customer whole will now be much higher than if the market had remained stable. In fact, there could be a gain if the market drops. It is clear, then, that market risk can magnify operational risk.

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There are also events that include both credit and operational risk elements. If a counterparty fails, and there was an operational error in securing adequate collateral, then the credit risk event is magnified by operational risk.

While market risk, credit risk, and operational risk functions are usually run separately, there are benefits in integrating these functions where possible. The overall risk profile of a firm depends not on the individual market, credit, and operational risks, but also on elusive strategic and reputational risks (or impacts) and the relationships among all of these risk categories.

Additional risk categories also exist—for example, geopolitical risk and liquidity risk. For these reasons, some firms adopt an enterprise risk man-agement (ERM) view of their risk exposure. It is important to consider the role of operational risk management as an element in ERM and to appreci-ate its relationship with all other risk types. The relationship among risks can be illustrated in Figure 1.1.

This ERM wheel illustrates that all risk types are interrelated and that central risk types can have an impact on risk types on the outer spokes of the wheel. For example a geopolitical risk event might result in risks arising in market risk, credit risk, strategic risk, liquidity risk, and operational risk.

Similarly, reputational risk or reputational impact can occur as a result of any risk event and so is at the center of the ERM wheel. This is just one possible model for the relationship between risk types and simply illustrates the complexity of effective ERM. Operational risk sits on the ERM wheel and is best managed and measured with that in mind.

figure 1.1 Enterprise Risk Management Wheel

Market

ERM

Reputational

GeopoliticalCreditOp

erational

LiquidityStrateg

ic

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Drivers Of OperatiOnal risk management

Operational risk management has arisen as a discipline as a result of drivers from three main sources: regulators, senior management, and third parties.

In addition to Basel II, there are other regulatory drivers for opera-tional risk management including Solvency II, which imposes Basel‐like requirements on insurance fi rms, and a host of local regulations such as the Markets in Financial Instruments Directive (MiFID) legislation in Europe and the Sarbanes‐Oxley Act (which includes risk and control requirements for fi nancial statements) in the United States. The regulatory evolution of operational risk is discussed in Chapter 2 .

Additional business drivers from within the banks and from third parties complement the many regulatory drivers of operational risk management. One of the most important of these additional drivers is that senior man-agement and the board both want to be fully informed of the risks that face the fi rm, including operational risk exposures. They are fully aware that operational risk events can have catastrophic fi nancial and reputational impact. An effective operational risk program should provide transparency of operational risk exposure to allow senior management to make strategic business decisions fully informed of the operational risk implications.

A strong operational risk framework provides transparency into the risks in the fi rm, therefore allowing for informed business decision making. With a strong operational risk framework, a fi rm can avoid bad surprises and equip itself with tools and contingency planning to be able to respond swiftly when an event does occur.

Furthermore, external third parties have started to ask about the opera-tional robustness of a fi rm.

Ratings agencies, investors, and research analysts are now aware of the importance of operational risk management and often ask for evidence that

eXample

A country’s government banned trades in a particular type of derivative. This ban could result in market risk (the value of the derivatives plum-mets), credit risk (counterparties who are concentrated in this product might fail), strategic risk (the business model might rely on growth in that product), and operational risk (certain activities might now be illegal).

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an effective operational risk framework is in place, and whether sufficient capital is being held to protect a firm from a catastrophic operational risk event.

key pOints

■ Operational risk is defined in Basel II as the risk of loss resulting from inadequate or failed processes, people and systems or from external events. This definition includes legal risk but excludes strategic and reputational risk.

■ Firms adapt the Basel II definition to their own needs. ■ Both qualitative and quantitative approaches are needed to effectively manage and measure operational risk.

■ Operational risk is a key element in an enterprise risk management (ERM) approach.

revieW QuestiOns

1. Which of the following best meets the Basel II definition of operational risk?a. A basket of options expires with a value of zero.b. A client refuses to pay his invoice.c. A wire transfer is sent to the wrong account.d. A government expropriates all foreign‐owned assets.

2. The main causes of operational risk are generally accepted to be:a. People, processes, systems, external eventsb. People, processes, systems, internal eventsc. Processes, systems, eventsd. People, events

nOtes

1. S644, International Convergence of Capital Measurement and Capital Standards: A Revised Framework, Bank for International Settlements, 2004.

2. JPMorgan Chase & Co. Annual Report, 2008, p. 117. 3. Deutsche Bank Financial Report, 2011, p. 110. 4. Footnote 90, supra. 5. See note 1.

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6. Citi Annual Report 2011, p. 106 7. As featured in issue 9 of Risk Universe and reproduced with their

permission. 8. www.independent.co.uk/news/uk/home‐news/things‐will‐go‐wrong‐as‐

london‐holds‐olympics‐says‐boris‐johnson‐7952706.html. 9. www.bbc.co.uk/sport/0/olympics/18906710#TWEET179228. 10. Annex 9, International Convergence of Capital Measurement and

Capital Standards: A Revised Framework, Bank for International Settlements, 2004.

11. http://edition.cnn.com/2012/08/01/sport/olympics‐badminton‐scandal/index.html.

12. www.bloomberg.com/news/2012‐07‐26/london‐olympics‐fake‐tickets‐create‐honeypot‐for‐criminals.html.

13. http://sports.yahoo.com/blogs/olympics‐fourth‐place‐medal/empty‐seats‐olympic‐venues‐prompt‐investigation‐224320331–oly .html.

14. www.billboard.biz/bbbiz/industry/legal‐and‐management/dis-pute‐between‐london‐olympics‐and‐musicians‐1007687952.story#I1ptQC1VdfjCF9xS.99.

15. www.ticketnews.com/news/natb‐calls‐london‐olympics‐ticket‐distribu-tion‐a‐failure081213258.

16. www.cbsnews.com/8301‐33747_162‐57473130/olympic‐security‐shortfall‐called‐absolute‐chaos/.

17. www.bbc.co.uk/news/uk‐england‐london‐18962856. 18. www.london2012.com/mm/Document/Publications/Annualre-

ports/01/24/09/33/locog‐annual‐report‐2010‐11.pdf. 19. www.london2012.com/about‐us/london‐prepares‐series/. 20. See note 8. 21. www.bbc.co.uk/sport/0/olympics/19023771. 22. S644, International Convergence of Capital Measurement and Capital

Standards: A Revised Framework, Bank for International Settlements, 2004.

c01.indd 14 9/4/2013 11:43:17 AM

The Road to RecoveryHow and Why Economic Policy Must ChangeAndrew Smithers978-1-118-51566-2 • Hardback • 360 pages • September 2013

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98

2

Why the Recovery Has Been So Weak

We are now suff ering from a weak and halting recovery. Chart 1 shows that among G5 countries only in Germany and the US has real GDP risen above the level that was achieved in the fi rst quarter of 2008. Both the UK and the US provide examples of how unusual the recession has been, both in terms of the slowness of the recov-eries and in the depths of the downturns. It has taken longer to recover to the previous peak in real GDP than on any previous occasion since World War II. Indeed, there are claims that the UK recovered more quickly in the 1930s than it has after the recent recession. 1 The US took four years from Q4 2007 to Q4 2011 to recover to its previous peak and the UK after four and half years has still not recovered to its Q1 2008 peak. In both countries the loss of output from peak to trough was the greatest seen in the post-war period, amounting to 6.3% of GDP for the UK and 4.7% for the US. 2

3

2 The worst previous post-war recessions were during the fi rst ( c. 1973–1976) and second oil shocks ( c. 1979–1983); neither their length nor their duration was as severe in either country as the post-shock recessions.

1 “ A funny way of fi ring up the locomotive ” by Sam Brittan, Financial Times (17th January, 2013).

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4 t h e r o a d t o r e c o v e r y

Chart 1. The Weak Recovery of G5 Countries. Sources: National Accounts via Ecowin.

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2008 2009 2010 2011 2012

GD

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The weak recovery has occurred despite the most aggressive attempt at stimulating the economy, in terms of both fi scal and monetary policy, that has been tried since World War II.

Interest rates were kept low in wartime, but then rose and have now fallen back to their lowest post-war level in nominal terms (Chart 2 ).

The pattern is similar, though more nuanced and less marked in real terms. Chart 3 shows that for both the UK and the US interest rates were very low in real terms after the war and after the oil shock, owing to high rates of infl ation. With these exceptions, current real interest rates and bond yields are at their lowest post-war levels.

Chart 4 shows that the pattern was the same for other G5 countries. Both real and nominal rates are exceptionally low and the fall in real rates is only constrained by the relatively low levels of infl ation.

As Chart 5 and Chart 6 illustrate, the Japanese, UK and US governments ’ defi cits have all risen to over 10% of GDP in recent years, while Germany ’ s budget is currently balanced. France ’ s defi cit

100

Why the Recovery Has Been So Weak 5

Chart 2. US: Interest Rates & Bond Yields. Sources: Federal Reserve & Reuters via Ecowin.

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Chart 3. US: Real Interest Rates & Bond Yields. Sources: Federal Reserve, Reuters & BLS via Ecowin.

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Chart 4. France, Germany, Japan & UK: Real Short-term Interest Rates. Sources: Reuters & Federal Reserve via Ecowin.

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Chart 5. France, Germany & Japan: Fiscal Defi cits. Source: OECD via Ecowin.

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102


peaked at 7.6% of GDP and is thought to have fallen to 4.5% of GDP in 2012.

Large defi cits have not therefore been successful in generating strong recovery. Nor has the growth of individual economies been associated with the size of their defi cits. Japan, which has the largest current defi cit, shares with the UK the wooden spoon for recovery, and Germany with no defi cit has achieved the best recovery along-side the US.

Neither fi scal nor monetary policy has therefore been successful in creating the growth rates that are generally assumed to be pos-sible. It follows that either the growth potential is less than assumed, the policies are correct but have not been pursued with suffi cient vigour or the policies are ill considered.

My view is that the policies have been the wrong ones and, although I am not alone in thinking this, my reasons seem very diff erent from those of other economists who share my conclusion. At the centre of the disagreement that I have with those who favour more stimulus is why the economy remains weak. The central issue is whether it is due to short-term, temporary problems, which are

Chart 6. UK & US: Fiscal Balances. Source: OECD via Ecowin.

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termed cyclical by economists, or structural ones which last longer and tend to be more intractable. The key diff erence between my views and the proponents of more stimuli is that I see today ’ s prob-lems as structural which need to be addressed with diff erent policies, while those who favour continuing the current medicine but upping the dosage assume that the problems are purely cyclical.

On the other hand I do not agree with those who see the structural problem as being a lack of output capacity. This in my view is overly pessimistic. There seems to be plenty of unused capac-ity in terms of both labour and capital equipment; the problem is that there are structural inhibitions to this capacity being used, without creating infl ation. We are not being held back by either a simple cyclical weakness in demand or a lack of capacity to grow: we have a new structural problem that we have not encountered before.

As I will seek to explain, the key structural inhibition that is preventing the spare capacity which we have in both labour and capital equipment from being fully used is the change in the way company managements behave, and this change has arisen from the change in the way managements are paid. There is abundant evi-dence that a dramatic change has taken place in the way those that run businesses are paid. Their incentives have been dramatically altered. It should therefore be of no surprise that their behaviour has changed, as this is the usual result of changed incentives.

For the economy as a whole, incomes and expenditure must be equal. No one can spend more than their income unless someone else spends less. If one company, individual or sector of the economy spends more than its income, it must fi nd the balance by selling assets or borrowing from somewhere else, and the company, indi-vidual or sector that lends the money or buys the asset must spend less than its income. A cash fl ow defi cit in one sector of an economy must therefore be exactly matched by a cash surplus in another. I am not here making a forecast but pointing to a necessary identity and one which it is essential to understand in order to comprehend the nature of the problem that we face in trying to bring govern-ment budget defi cits under control.

Although much that is forecast is not very likely, almost anything in economics is possible, subject only to the essential condition that the fi gures must add up. This is always important, and often neglected

104


by forecasters, but it is particularly informative when a large reduc-tion in fi scal defi cits is essential. This is because any reduction in fi scal defi cits must be exactly matched by reductions in the com-bined cash surpluses of the household, business and foreign sectors. When the defi cits fall, the cash surpluses of these other sectors of the economy must fall by an identical amount. The OECD estimates that in 2012 the UK and US economies had government budget defi cits, which are also known as fi scal defi cits, equal to 6.6% and 8.5% of GDP respectively. To prevent a dangerous and unsustainable situation arising in which the ratios of national debts to GDP are on a permanently rising path, these fi scal defi cits must be brought down to about 2% or less of GDP. It follows, as a matter or identity, that the surpluses in the household, business and foreign sectors of the economies must fall by around 4.6% of GDP for the UK and 6.5% for the US from the level estimated by the OECD in 2012.

One of the major lessons of history is that economies must from time to time adjust to large changes and can do so without disaster, provided that the speed at which they are required to adjust is not too rapid. It will therefore be very important to make sure that there are smooth rather than abrupt declines in the fi scal defi cit and thus in the matching declines of other sectors ’ cash fl ows. Unfortunately, ensuring that the adjustment is smooth is also likely to be very dif-fi cult. This is partly because the economy is unpredictable and partly because political decisions are often wayward. But it is also because the impact is likely to fall mainly on the business sector, and, if the hit is too sharp, companies are likely to respond by reducing invest-ment and employment, thus causing another recession. The probabil-ity that a reduction in the fi scal defi cit will fall most heavily on the business sector is shown both by past experience and from consider-ing the contributions that are likely from other sectors.

In the past, changes in the fi scal balances of the major Anglo-phone economies have moved up and down with fl uctuations in the business sector ’ s cash fl ow, as I illustrate in Chart 7 for the UK and for the US in Chart 8 . 3 On historical grounds, therefore, the

3 The correlation coeffi cient between business cash fl ow and the fi scal defi cit is 0.71 for the UK and 0.83 for the US. In each case we measure the relationship for the whole period for which we have data, which are annual from 1987 to 2011 for the UK and quarterly from Q1 1960 to Q3 2012 for the US.

105


Chart 7. UK: Budget Defi cits & Business Cash Surpluses Go Together. Source: ONS (EAOB, NHCQ & YBHA).

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Chart 8. US: Budget Defi cits & Business Cash Surpluses Go Together. Sources: NIPA Tables 1.1.5 & 5.1.

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106


scale of the reductions required in the fi scal defi cits means that large compensating falls in the cash surplus of the business sectors will be needed.

As Chart 7 and Chart 8 show, companies in both the UK and the US are currently running exceptionally large cash surpluses. It is the existence of these surpluses as well as their size which is unusual. As Table 1 shows, until recently companies have tended to run cash defi cits. It is only over the past decade that companies have been producing more cash than they pay out, either to fi nance their spending on new capital investments or to pay out dividends.

The regular cash defi cits shown before 2001 are the expected pattern. The business sector normally fi nances itself partly from equity and partly from debt. The extent to which companies fi nance their business by debt compared to equity is called their leverage. If, for example, half of companies ’ fi nance comes from borrowing and the rest from equity, the ratio of debt to equity will be 100%, i.e. debt and equity will have equal values. There are limits to the extent that companies can fi nance themselves with debt. Their lever-age rises as the proportion of fi nance from debt rises, and as this ratio becomes higher so does the risk that lenders will lose money when the economy falls into recession. This puts a limit on the extent to which companies can fi nance themselves with debt, but this limit is not fi xed. If lenders don ’ t fi nd that they are experienc-ing losses from bad debts, they assume that current leverage ratios are conservative and are willing to lend on the basis of even higher ratios of debt to equity. But this is a dangerous process, because high leverage increases the risks of a fi nancial crisis and the risks that it will cause a deep recession.

Leverage can vary a lot over time, and I will be showing later that business debt had risen to unprecedented heights prior to the fi nancial crisis. It has since fallen a little but remains nearly at record

Table 1. Business Cash Flow Surpluses ( + ) or Defi cits ( − ) as % of GDP (Sources: ONS & NIPA )

UK US

1987 to 2001 − 1.65 1960 to 2001 − 0.852002 to 2011 4.54 2002 to 2011 3.34

107


levels and it is almost certain that it is still dangerously high. We should therefore wish to see leverage falling and thus see equity providing a higher proportion of companies ’ fi nancial requirements than has been the case in recent years.

It is easy to see how the growth of the economy can be fi nanced by a mixture of equity and debt. In a long run stable situation the leverage ratio will also be stable. If debt and equity each provide half the capital needed, this will also be the ratio by which new investment is fi nanced. However, the proportion of new investment that needs to be fi nanced with equity will always be a large one. If, for example, over the long-term, investment is fi nanced 60% by debt and 40% by equity, rather than 50% by each, the leverage rises sharply. In the fi rst example debt will equal 100% of equity and in the second it will be 150%. This measure of leverage would thus be 50 percentage points higher than if the proportions fi nanced by debt and equity had remained equal. In practice things can be more complicated, but the broad outline is nonetheless clear. Over time the capital stock must grow if the economy is to expand and, over the long-term, companies must therefore add to their equity capital at a steady rate. This equity capital is equal to the value of compa-nies ’ assets less the amount that they have borrowed to fi nance them and is also known as net worth.

Equity rises from operations if companies pay out less than 100% of their after-tax profi ts as dividends and falls if they pay out more. Equity can also be increased by new issues and will fall if companies buy back their own shares or acquire other companies using cash or debt. Companies either run down their cash or increase their debt when they buy back their own shares, and this often occurs when they acquire other companies. It is possible to fi nance acquisitions with the whole cost being met by equity through companies using their own shares. In recent years compa-nies have been using debt to fi nance acquisitions of their own and other companies ’ shares to a much greater extent than they have been making new equity issues and they have also, of course, been paying dividends. By adding up the sums of money spent on buy-backs, acquisitions and dividends, and deducting any amount raised from new issues, we know the total amount of cash that companies are paying out to shareholders.

Continues...

Code RedHow to Protect Your Savings From the Coming CrisisJohn Mauldin & Jonathan Tepper978-1-118-78372-6 • Hardback • 304 pages • November 2013

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109

13

Chapter One

The Great Experiment

Like gold, U.S. dollars have value only to the extent that they are strictly limited in supply. But the U.S. government has a technology, called a printing press (or, today, its electronic equivalent) that allows it to produce as many U.S. dollars as it wishes at essentially no cost. By increasing the number of U.S. dollars in circulation, or even by credibly threatening to do so, the U.S. government can also reduce the value of a dollar in terms of goods and services, which is equivalent to raising the prices in dollars of those goods and services.

—Ben Bernanke, Chairman of the Board of Governors of the Federal Reserve Bank of the United States

P resident Lyndon B. Johnson once summed up the general feeling about economists when he asked his advisers, “Did you ever think that making a speech on economics is a lot like pissing

down your leg? It seems hot to you, but it never does to anyone else.” Reading a book about monetary policy and central banking can seem equally unexciting. It doesn ’t have to be.

Central banking and monetary policy may seem technical and bor-ing; but whether we like it or not, the decisions of the Federal Reserve, the Bank of Japan (BoJ), the European Central Bank (ECB), and the

c01.indd 13 18-09-2013 09:49:18

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Bank of England (BoE) aff ect us all. Over the next few years they are going to have profound impacts on each of us, touching our lives in every way. They infl uence the value of the dollar bills in our wallets, the price of the groceries we buy, how much it costs to fi ll up the gas tank, the wages we earn at work, the interest we get on our savings accounts, and the health of our pension funds. You may not care about monetary policy, but it will have an impact on whether you can retire comfortably, whether you can send your children to college with ease, or whether you will be able to aff ord your house. It is diffi cult to over-state how profoundly monetary policy infl uences our lives. If you care about your quality of life, the possibility of retirement, and the future of your children, you should care about monetary policy.

Despite the importance of central bankers in our lives, outside of trading fl oors on Wall Street and the City of London, most people have no idea what central bankers do or how they do it. Central bankers are like the Wizard of Oz, moving the levers of money behind the scenes, but remaining a mystery to the general public.

It is about time to pull the curtains back on monetary policy making. Even though they are separated by oceans, borders, cultures, and

languages, all the major central bankers have known each other for decades and share similar beliefs about what monetary policy should do. Three of the world ’s most powerful central bankers started their careers at the Massachusetts Institute of Technology (MIT) econom-ics department. Fed chairman Ben Bernanke and ECB president Mario Draghi earned their doctorates there in the late 1970s. Bank of England governor Mervyn King taught there briefl y in the 1980s. He even shared an offi ce with Bernanke. Many economists came out of MIT with a belief that government could (and, even more important, should) soften economic downturns. Central banks play a particularly important role, not only by changing interest rates but also by manip-ulating the public ’s expectations of what the central bank might do.

We are living through one watershed moment after another in the greatest monetary experiment of all time. We are all guinea pigs in a risky trial run by central bankers: it ’s Code Red time.

Those of us who are of a certain age remember the great Dallas Cowboys coach Tom Landry. He would stalk the sidelines in his fedora, holding a sheet of paper he would consult many times. On it were the

c01.indd 14 18-09-2013 09:49:18

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The Great Experiment 15

plays he would run, worked out well in advance. Third down and long and behind 10 points? He had a play for that.

The Code Red policies that central bankers are coming up with more closely resemble Hail Mary passes than they do Landry ’s carefully worked out playbook: they are not in any manual, and they are cer-tainly not normal. The head coaches of our fi nancial world are sending in one novel play after another, really mixing things up to see what might work: “Let ’s send zero interest rate policy (ZIRP) up the middle while quantitative easing (QE) runs a slant, large-scale asset purchases (LSAPs) goes deep, and negative real interest rates, fi nancial repres-sion, nominal gross domestic product (GDP) targeting, and foreign exchange intervention hold the line.”

The acronym alphabet soup of the playmakers is incomprehensi-ble to the average person, but all of these programs are fancy, technical ways to hide very simple truths.

In Through the Looking Glass , Humpty Dumpty says, “When I use a word, it means just what I choose it to mean—neither more nor less.” When central bankers give us words to describe their fi nancial policies, they tell us exactly what they want their words to mean, but rarely do they tell us exactly the truth in plain English. They think we can ’t handle the truth.

The Great Financial Crisis of 2008 marked the turning point from conventional monetary policies to Code Red type unconventional policies.

Before the crisis, central bankers were known as boring, conservative people who did everything by the book. They were generally disliked for being party poopers. They would take away the punch bowl just when the party got going. When the economy was overheating, central bank-ers were supposed to raise interest rates, cool down growth, and tighten monetary policy. Sometimes, doing so caused recessions. Taking away the punch bowl could hardly make everyone happy. In fact, at the start of the 1980s, former chairman Paul Volcker was burnt in effi gy by a mob on the steps of the capitol for hiking short-term interest rates to 19 percent as he struggled to fi ght infl ation. Central bankers like Volcker believed in sound money, low infl ation, and a strong currency.

In the throes of the Great Financial Crisis, however, central bank-ers went from using interest rates to cool down the party to spiking

c01.indd 15 18-09-2013 09:49:19

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the punch with as many exotic liqueurs as possible. Ben Bernanke, the chairman of the Federal Reserve, was the boldest, most creative, and unconventional of them all. With his Harvard, MIT, and Princeton background, he is undoubtedly one of the savviest central bankers in generations. When Lehman Brothers went bust, he invented dozens of programs that had never existed before to fi nance banks, money mar-ket funds, commercial paper markets, and so on. Bernanke took the Federal Funds rate down almost to zero, and the Fed bought tril-lions of dollars of government treasuries and mortgage-backed secu-rities. Bernanke promised that the Federal Reserve would act boldly and creatively and would not withdraw the punch bowl until the party was really rolling. Foreign central bankers like Haruhiko Kuroda (BoJ); Mervyn King and his replacement from Canada, Mark Carney (BoE); and Mario Draghi (ECB) have also promised to do whatever it takes to achieve their objectives. We have no doubt that whoever replaces Bernanke will be in the same mold.

These are the days of a new breed of central banker who believes in the prescription of ultra-easy money, higher rates of infl ation, and a weaker currency to cure today ’s ills. Their experimental medicine may have saved the patient in the short term, but it is addictive; withdrawal is ugly; and because long-term side eff ects are devastating, it can be prescribed only for short-term use. The problem is, they can ’t openly admit any of that.

Central bankers hope that unconventional policies will do the trick. If everything goes as planned, infl ation will quietly eat away at debt, stock markets will go up, house prices will go up, everyone will feel wealthier and spend the newfound wealth, banks will earn lots of money and become solvent, and government debts will shrink as taxes rise and defi cits evaporate. And after all is well again, central banks can go back to the good old days of conventional policies. There is no guarantee that will happen, but that ’s the game plan.

So far, Code Red policies have lifted stock markets, but they have not worked at reviving growth. But Code Red–type policies are like a religion or communism. If they don ’t work, it is only proof that they were not tried in suffi cient size or with enough vigor. So we ’re guaran-teed to see a lot more unconventional policies in the coming months and years.

c01.indd 16 18-09-2013 09:49:19

113


How I Learned to Stop Worrying and Love Infl ation

The Great Financial Crisis was a story of a huge mountain of debt that was piled too high, reached criticality, and then collapsed. For decades, families, companies, and governments had accumulated every kind of debt imaginable: credit card bills, student loans, mortgages, corporate and municipal bonds, and so on. Once the mountain rumbled, broke, and started to collapse, the landslides spread everywhere. The epicenter of the crisis was the U.S. subprime mortgage market (in fact, many for-eign leaders still think it was fat, suburban, Big Mac–eating Americans who caused the global crisis), but the United States was just a small part of a much bigger problem. Countries such as Ireland, Spain, Iceland, and Latvia also had very large real estate bubbles that burst. Other countries, including Australia, Canada, and China, have housing bubbles that are still in the process of bursting. It ’s the same problem everywhere: too much debt that cannot be paid back in full.

(We certainly would not minimize the role of the Federal Reserve in failing to supervise the banks and especially subprime debt. By hold-ing interest rates too low for too long and by willfully ignoring the developing bubble in the U.S. housing market, they certainly played a central role.)

When a person has too much debt, the sensible thing to do is to spend less and pay down the mortgage or credit card bills. However, what is true for one person isn ’t true for the economy as a whole. Economists call this principle the paradox of thrift . Imagine if everyone decided overnight to stop spending beyond what was absolutely neces-sary, save more, and pay down their debts. That would mean fewer din-ners out, fewer visits to Starbucks, fewer Christmas presents, fewer new cars, and so on. You get the picture. The economy as a whole would contract dramatically if everyone spent less in order to pay down debts. But, in fact, that is exactly what happened during the Great Financial Crisis. Economists call this process deleveraging . And the last thing cen-tral banks want is for everyone to stop spending money and reduce their debts at the same time. That leads to recessions and depressions.

At least that was the theory proposed by John Maynard Keynes, the father of one of the most infl uential economic schools of thought,

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18 c o d e r e d

and it has become the reigning paradigm. It ’s all about encouraging consumption and reviving “animal spirits.” If the economy is in the doldrums (recession), it is up to the government to run defi cits, even massive ones, in order to “prime the pump.” Put plenty of money into people ’s hands so they will go out and spend, encouraging businesses to expand and hire more workers, who will then consume yet more goods, and so on. Wash, rinse, and repeat.

Another solution if you have too much debt is to declare bank-ruptcy. In many countries that can be an eff ective way of starting over again. You put behind you debts you can ’t pay, off er to pay what you can, and start anew. Once again, what is good for the individual isn ’t necessarily good for the economy as a whole. Imagine what would happen if millions of people declared bankruptcy at the same time. Banks would all go bust, and the government would probably have to pick up the tab and recapitalize the banks. And then, before long, the government would fi nd itself going bust.

The diff erence between what is right for one person and what is right for society is paradoxical. It is what logicians call the fallacy of com-position . What is true for a part is not true for the whole. If you drive to work 10 minutes early, you might avoid traffi c. If everyone drives to work 10 minutes early, the traffi c jam will happen 10 minutes earlier. Central banks don ’t want everyone to be prudent or to go bankrupt at the same time. They would simply prefer everyone to remain calm and carry on spending.

If you want to avoid everyone ’s ceasing to spend—or, worse yet, everyone ’s going bankrupt at the same time—the only way to make the debt go away in real terms is through infl ation. Infl ation is the Ghostbusters of debt. It wipes debt out over time. For the sake of sim-plicity, imagine that you owe $100,000. If infl ation is 2 percent, it will take about 30 years to cut the value of the loan in half. But if the rate of infl ation doubles to 4 percent, it will take just 18 years to halve the value of the loan. And if infl ation doubles again to 8 percent, you will halve the loan in 8 years!

Infl ation is just what the doctor ordered for an economy with too much debt. By ratcheting up infl ation, central bankers can erode debt quickly and quietly. But while infl ation is the friend of debtors, it is the enemy of savers; so for central bankers to come out and say they ’re

c01.indd 18 18-09-2013 09:49:19

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in favor of infl ation would be like the pope ’s announcing one day that he ’s not Catholic. That isn ’t going to happen.

Infl ation is a subject that divides economists because it means dif-ferent things to diff erent people. Not all infl ation is bad. Infl ation is generally considered to be problematic when the broad price level of most goods and services starts to go up because too much money is chasing too few goods. The increase in the price of a haircut is bad infl ation. The method of cutting hair is no diff erent than it was in the 1930s or the 1950s, yet it is vastly more expensive to get your hair cut today. (I [ John] pay 200 times more for a haircut today than I did when I was a kid.) However, an increase in the price of a Picasso or de Kooning is considered to be normal, or “good,” infl ation. The higher prices are merely a refl ection of more wealthy people in the world chasing fi ne art. They refl ect the scarcity of the goods for sale and the laws of supply and demand at work. And who complains about the asset infl ation of a rising stock market or rising home values?

Then there is good defl ation and bad defl ation. The defl ation of falling telegraph, telephone, or Internet prices is viewed as good. Better technology means that prices fall because we can do the same things more cheaply or even nearly for free. For example, in Money, Markets & Sovereignty , Benn Steil and Manuel Hinds describe the second phase of the Industrial Revolution in the United States between 1870 and 1896. Prices fell by 32 percent over the period, but real income soared 110 percent amid robust economic growth, expanded trade, and enor-mous innovation in telecommunications and other industries.

The bad kind of defl ation is diff erent. When demand drops because people have too much debt and not enough money to spend, prices fall, too, though the cost of production does not. Jobs dry up, leaving people with even less to spend. That is the kind of defl ation central bankers fear today.

Alphabet Soup: ZIRP, QE, LSAP

Let ’s look at how central bankers attempt to create infl ation and how they help households, companies, and governments burdened with too much debt. We ’ll go through the main acronyms and technical terms and explain what they mean and how they aff ect you.

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The main way monetary authorities have an impact on the econ-omy is by setting interest rates. Interest rates determine the price at which people will borrow and lend. In the old days, when the econ-omy was growing quickly, central banks would raise rates. When the economy was slowing, they ’d cut rates, which meant that fi nancing got cheaper, credit was easier, and money was looser.

The reason the Fed cut interest rates was to stimulate the economy. Lower rates mean lower mortgage, credit card, and car payments. They give businesses access to cheaper capital and hopefully spur profi ts and thus hiring. This puts more money into the hands of consumers. As an example, U.S. 30-year mortgage rates recently hit a record low of 3.66 percent, down from 4.5 percent the same time last year. A number of mortgage holders will refi nance, given the much lower rates, increasing their disposable income. That almost makes us want to buy a house or two. Who can complain about a free lunch?

Cutting rates can only go so far until you hit zero. Then you ’re stuck with a fl oor. In fact, central banks cut rates during the fi nancial crisis, and then left them near zero and have not raised them since. Leaving rates at or near zero is what central banks refer to as zero interest rate policy (ZIRP). Currently, the United States, United Kingdom, Japan, Switzerland, and, arguably, the Euro area are all engaging in ZIRP.

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Figure 1.1 Global Interest Rates Source: Variant Perception , Bloomberg.

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In a ZIRP world, debtors are overjoyed and savers are screwed. Imagine borrowing at 5 or 10 percent and then suddenly seeing your borrowing costs fall to a little above zero. No matter how much debt you had before, paying very little interest every month is a lifesaver. Low borrowing costs make it easier for struggling businesses to roll over their debt and reduce the real value of debt payments. If you reduce the coupon payment on a loan, that is economically the same thing as forgiving part of the principal amount, but this forgiveness is hidden. The low rates eff ectively allow “zombie” households and busi-nesses to limp along without going bankrupt.

Near-zero interest rates are, however, terrible for savers, investors, and lenders. Imagine you ’re a retiree, and you ’ve been responsible and saved all your life; you ’ve put money in the bank that you expect to pay you interest every month. You probably bought some bonds as well so you could collect coupons every quarter. In a ZIRP world, you would be getting very little every month from interest and coupon payments. You would live your retirement years with far less income than you had planned for, or you would need to work far longer in order to save more.

This is happening to retirees all over the world—it ’s why more and more people over 60 are still working. The Federal Reserve and cen-tral bankers are not particularly worried about savers. Most Americans are struggling with debt. In an indebted society, helping debtors beats helping savers.

Infl ation is the opposite of a gift that keeps on giving. Higher infl ation allows the Federal Reserve and other central banks to take real interest rates below zero. Nominal interest rates are the actual interest rate you get. Real interest rates are nominal rates minus the infl ation rate. If your bank off ers you 2 percent on your bank account, the nominal rate is 2 percent. So far, so simple. If infl ation is 2 percent, then the real interest rate is 0 (2 − 2 = 0). The interest rate is only just keeping up with infl ation. If infl ation is 4 percent, then the interest you are getting on your bank account isn ’t even keeping pace with infl ation. Your real interest rate would be negative 2 (2 − 4 = −2). As you can see, with rates near zero, as long as infl ation is positive, central banks can create negative real rates. Even though nominal rates can be trapped at zero, real interest rates can go below zero.

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When real rates are negative, cash is trash. Negative real rates act like a tax on savings. Infl ation eats away at your money, and is in eff ect a tax by the (unelected!) central bankers on your hard-earned money. Leaving money in the bank when real rates are negative guarantees that you will lose purchasing power. Negative real rates force savers and investors to seek out riskier and riskier investments merely to tread water. It almost guarantees people don ’t save and stop spending. In fact, Bernanke openly acknowledges that his low interest-rate policy is designed to get savers and investors to take more chances with riskier investments. The fact that this is precisely the wrong thing for retirees and savers seems to be lost in their pursuit of market and economic gains.

Simply by opening their mouths, central bankers can aff ect not only today ’s interest rate, but tomorrow ’s expected interest rate as well. If Bernanke (and his successors) or Mario Draghi of the ECB promise to keep interest rates near zero until kingdom come, investors will gener-ally take them at their word. By promising to keep rates low, central banks have crushed bond yields. The bond yield curve tells the story. The yield curve is the structure of interest rates for bonds for today, tomorrow, and the day after tomorrow. By plotting a line for each bond maturity, you can see what expected rates are out into the future: 2 years, 5 years, 10 years, and 30 years. The U.S. government can now issue 10-year debt for less than 2 percent yield. This is below the rate of infl ation. It implies the Fed has been successful at keeping rates below infl ation all the way out to 10 years.

Lots of big economists such as Paul Krugman, Ben Bernanke, Gauti Eggertsson, and Michael Woodford, have provided the intellec-tual underpinnings that justify Code Red policies (the list of names is actually quite long). They argued that if unconventional monetary pol-icy can raise expected infl ation, this strategy can push down real inter-est rates even though nominal rates cannot fall any further (i.e., they can ’t fall below zero). Read their research and bear that in mind when these same economists say they don ’t want to create infl ation.

Government bonds used to off er a risk-free rate of return. You took no risk in buying them, and you were guaranteed a return. Jim Grant, the astute fi nancial analyst, has noted that bonds have rallied so much, and the yields on government bonds are so low, that they now off er investors return-free risk : you ’re now guaranteed a loss buying

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government bonds. Coupons are so low that investors are not even being compensated at the rate of infl ation. It is hard to see how rates can go much lower or how more fools can be found to buy the bonds. The only people who buy British, Japanese, German, or American gov-ernment bonds today in any size are institutions that are legally forced to do so, like insurance companies and pension funds.

From a central banker ’s point of view, leaving interest rates near zero is useful, but it has given them little direct infl uence over the econ-omy. They can control rising infl ation and expectations of higher prices only indirectly. However, central banks still have more bullets in the chamber they can use.

Quantitative Easing, a.k.a. Money Printing

In addition to manipulating interest rates, central banks have the abil-ity to increase the money supply through quantitative easing (QE). Despite all the syllables, that ’s just a fancy way to say money print-ing. When the Fed wants to print new money and expand the money supply, it goes out and buys government bonds from banks that it has designated as “primary dealers.” The Fed takes delivery of the securi-ties and pays the dealers with newly printed money. The money goes into the dealers ’ bank accounts, where it can then support lending and money creation by the banking system. Likewise, when the Fed wants to reduce the money supply, it sells bonds back to the banks. The bonds go to the dealers, and the money paid to the Fed simply disappears. (As you can see, both “printing” money and making money disappear happen electronically and instantly. No actual printing of currency is involved. No trees are harmed in the process.)

Banks absolutely love QE—it is a gift to them, and it ’s one that circumvents the congressional appropriations process. To pay for QE, the Fed credits banks with electronic deposits that are reserve bal-ances at the Federal Reserve. These reserve balances have ballooned to $1.5 trillion, from a mere $8 billion in late 2008. The Fed now pays 0.25 percent interest on reserves it holds, which amounts to nearly $4 billion a year in the banks ’ coff ers. If interest rates rise to 3 percent, and the Federal Reserve then raises the rate it pays on reserves

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correspondingly, the interest payment will rise from $4 billion to $45 billion a year—an even larger gift! And that is one of the reasons why people are so worried about what will happen if the Fed ever goes back to a normal policy regime. Will the primary dealers lose their interest ben-nies? Will the Fed actually raise reserve rates? Or will the Fed reduce the money supply, taking away profi ts of the banks? There is a reason the mar-kets are worried, and it has to do with profi ts. Their profi ts. Stay tuned.

The Fed has done over $1.5 trillion of money printing via QE. It is set to do a lot more. See Figure 1.2 for the projected growth of the Fed ’s balance sheet. It resembles a Nasdaq stock in 1999, shoot-ing to the moon. You would think that $1.5 trillion might be enough, but many respected economists and writers such as Paul Krugman and Martin Wolf are calling for even more QE. When you hear pundits calling for even more QE, you can almost conjure reruns of old Star Trek episodes, with Captain Kirk—make that Captain Ben—shouting, “Dammit, Scotty, you ’ve got to give me more QE!” as the Fed tries to escape a black hole of high debt and low growth.

Every time a central bank prints money, it creates winners and los-ers. So far, the biggest benefi ciaries of money printing are governments themselves. This should come as no surprise. (To paraphrase Captain Renault in Casablanca , “I ’m shocked, shocked to fi nd that money printing is going on in here!”) Central banks everywhere are printing

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Figure 1.2 Projected Growth of the Federal Reserve ’s Balance Sheet Source: Variant Perception , Bloomberg.

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money to fi nance very large government defi cits. In fact, in 2011, the Federal Reserve fi nanced around three quarters of the U.S. defi cit; in 2012, it fi nanced over half of it; and in 2013, it will fi nance most of it. Why borrow money from real savers when the central bank will print it for you?

The problem for savers and investors is that all the major central banks are in on the act. Take a look at Figure 1.3 and you can see that it isn ’t just the Fed. It is the BoJ, the BoE, the Swiss National Bank, and even the ECB that have expanded their balance sheets. In the case of Japan and England, the central banks are buying bonds outright. The Europeans are not buying bonds directly, but they ’ve provided unlim-ited fi nancing for private banks to do so. And the Swiss have been buying loads of everyone else ’s bonds to keep their currency from appreciating. It ’s a lollapalooza of money creation.

Since printing the money to buy government bonds costs noth-ing (given that central bank money is just bytes on a computer some-where), governments get money for nothing and their checks for free. The central bank buys government bonds in the open market rather than from the government directly, and the pretense of an arm ’s-length transaction between government and central bank maintains

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Figure 1.3 Central Bank Balance Sheets Shoot Up to the Moon Source: Variant Perception , Bloomberg.

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the illusion of central bank independence, with all parties claiming a separation of monetary and fi scal policy. But that ’s just for show. By essentially issuing bonds to itself, the government appears to raise rev-enue miraculously, without burdening anyone else. Yet free money is like a unicorn that leaves trails of tasty chocolate droppings wherever it goes: it exists only in the realms of fantasy. (You or I might simply say, “There are no free lunches”; but as John Maynard Keynes put it, “Words ought to be a little wild, for they are the assaults of thoughts on the unthinking.”)

Since there can actually be no such thing as a government rais-ing revenue at no cost, simple logic tells us that someone has to pay. It is impossible to know in advance who will pay for a central bank ’s “free lunch,” only that someone, somewhere will eventually pay. So governments are using quantitative easing to raise revenues with-out even knowing upon whom the burden will fall (let alone telling them). Compare this to raising revenue the normal way, by taxation. It is possible to know who raised the tax, when it was levied, when it is payable, and how much has to be paid. The burden of money printing, however, falls on unsuspecting victims. These are generally creditors, savers, and investors, but the costs are even more widely felt. It is easy for your local politician to deny culpability—the cen-tral bank is by design out of his control. (Well, except in Japan these days. Things like central bank independence can change when sur-vival is at stake.)

Extremely high government spending would be diffi cult with-out central bank fi nancing. As the book goes to press, for every dol-lar that the U.S. federal government spends, it borrows 40 cents (and that has been the case for some time). To put this in everyday terms, in 2012 the median American household income was $50,054. If a nor-mal American family ran its budget like the U.S. government, it would borrow about $20,000 a year to pay for expenses. Most households would love to print money to fi nance their spending. By printing money, the Federal Reserve lends a helping hand to ease spending. (If the Federal Reserve is reading this, any money printing sent our way would be much appreciated. Please call for our bank account details. We promise to spend any such money immediately and thus do our part to drive up consumer spending.)

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The biggest winners from the Fed ’s policies have been stockhold-ers. The job of all central bankers is to keep prices stable. In the case of the Fed, it also has the job of promoting full employment in the econ-omy. The two missions are referred to as the “Dual Mandate.” However, in a Code Red world, the central banks have created a third mandate for themselves: make stock prices go up through large-scale asset pur-chase (LSAP) programs. Bernanke spoke directly about this in a speech in January 2011:

Policies have contributed to a stronger stock market just as they did in March 2009, when we did the last iteration of this. The S&P 500 is up 20 percent-plus and the Russell 2000, which is about small cap stocks, is up 30 percent-plus.

He returned to the theme in a speech in 2012.

LSAPs also appear to have boosted stock prices, presumably both by lowering discount rates and by improving the eco-nomic outlook; it is probably not a coincidence that the sus-tained recovery in U.S. equity prices began in March 2009, shortly after the FOMC ’s decision to greatly expand securi-ties purchases. This eff ect is potentially important because stock values aff ect both consumption and investment decisions.

These remarks are vintage Bernanke. If you ’re an investor or specu-lator, the message is loud and clear: Buy stocks. We ’ve got your back. (But let ’s see who takes the blame when the stock market falls next time. Just saying . . .)

The reason the Fed wants stock prices to go up is that when stocks go up, investors are happy and likely to spend more money. It is trickle-down monetary policy. QE, ZIRP, and LSAPs to the tune of $85 bil-lion of purchases a month are pumping up the stock market, all with the hope that rich people will spend those gains, and that money will trickle down to the rest of the country. So far, no dice. (As we write this, new jobs created per month in the United States are around 150,000, so it takes about $500,000 of QE to create one job. Bravo to the Fed!! It would be far easier to simply write the unemployed checks for $100,000. That would be 80 percent cheaper.)

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The problem is that there is no clear link between developments in fi nancial markets and the real economy. Research now points to the problem: the “wealth eff ect” from a rise in the stock market is quite small. Higher stock market prices tend to benefi t only the few who were already wealthy. The same economists who despise supply-side economics are madly infatuated with supply-side monetary policy. Go fi gure. Trickle-down monetary policy indeed!

Most Americans own stocks, but only the wealthiest 10 percent of the population own signifi cant amounts of stocks. Their retirement accounts are worth an average $277,000. But middle-income families have just $23,000 in their accounts, and the poor have nothing at all. The rich were almost all employed before quantitative easing anyway. Afterwards, they still have jobs and are richer. As for the poor, they still have very high unemployment and have not benefi ted in the slightest from a higher stock market.

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Figure 1.4 QE and LSAPs Have Been Very Bullish for Stocks Source: Variant Perception , Bloomberg.

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Debasing Your Currency

In a world of zero interest rates, negative real rates and quantitative eas-ing, money has less and less value. Central bankers are perfectly aware of this, and they ’ve discussed it in public. In fact, devaluing the dollar is a very explicit goal. In a speech in 2002 Ben Bernanke admitted that creating money electronically would immediately devalue the dollar. As he argued:

Like gold, U.S. dollars have value only to the extent that they are strictly limited in supply. But the U.S. government has a technology, called a printing press (or, today, its electronic equivalent) that allows it to produce as many U.S. dollars as it wishes at essentially no cost. By increasing the number of U.S. dollars in circulation, or even by credibly threatening to do so, the U.S. government can also reduce the value of a dollar in terms of goods and services, which is equivalent to raising the prices in dollars of those goods and services.

The Obama administration is thrilled with a weaker dollar. Christina Romer, former chair of the Council of Economic Advisers, also noted that, “Quantitative easing also works through exchange rates.” She argued that the Fed could engage in much more aggressive QE to further lower the dollar, if needed. We will return later to the point that this makes it hard to object when Japan does the same thing but just twice as intensively!

While devaluing the dollar might seem like an insane idea to a normal person, it is exactly what some central banks want. Weakening your currency is a tried and tested strategy that countries have used throughout the years. Central bankers who weaken their currencies are like drag racers that inject nitrous oxide into their engines. It is like cheating and can give an economy a little extra push in the race for economic growth. The fact that is bad for the long-term survival of their engines is lost in the drive to win the race today.

Many countries rely on exports or would like to export more to grow. A weaker currency makes goods and services more appealing

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to foreigners. For example, a few years ago, when the pound had an exchange rate of $2.10 against the dollar, lots of British women traveled to New York for the weekend to buy handbags and eat out. But when the pound bought only $1.35 worth of goods, no one hopped from London to the United States to go shopping. On a very large scale, the same happens. For a U.S. auto maker, selling cars to for-eigners gets a lot easier if the dollar is weak against foreign currencies.

When a currency appreciates, exports can be hit very hard. It ’s tougher to sell computers, cars, and ships to foreigners, and so most countries and their businesses want a weak currency. It is easier for a business to sell products when their currency is dropping than it is to become more productive. Politicians may say they want a strong dollar or a strong euro, but in practice the opposite is true. (Watch what they do, not what they say.)

Devaluing your currency sounds wonderful in theory. In prac-tice, it doesn ’t always work out as planned. Central bankers, like drag racers, can inject nitrous oxide into their engines to get a little more horsepower. If you are the only one doing it, you ’ll have an edge. The problem is that if everyone is doing it, no one has an advantage. And eventually, everyone burns out their engines and no one wins. Despite the initial optimism they may inspire, in the long run currency cri-ses can only lead to stagnation, infl ation, falling standards of living, and poor growth.

Navigating a Code Red World

Whenever central bankers spike the punchbowl through money print-ing or currency devaluations, investors are happy. Every QE announce-ment has made stocks go up. Every major currency sell-off , whether it is the dollar or, lately, the Japanese yen, has lifted stock markets and commodities like oil, copper, wheat, and corn in the terms of the cur-rency being trashed—er, we mean devalued. The policy of very low interest rates and money printing appears to have worked, up to this point. Most stock markets have doubled from the lows they hit after Lehman Brothers went bankrupt. The euphoria of investors should come as no surprise. When Nixon took the dollar off the gold standard

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in 1971, stocks skyrocketed. But investors should recall that the joy was short-lived. As it turned out, the 1970s were one of the worst decades for investing in stocks or bonds. Commodities did well for a while and then crashed. Investing was treacherous. The near future will likely be equally tumultuous, marked by bubbles, booms, and busts; and investors will need to be prepared.

For many investors, the last few years have been a stormy voyage. It is easy to feel like a medieval explorer sailing through uncharted waters into terra incognita beyond the edge of the map.

In a memorable (and relevant!) scene from Blackadder , one of our favorite comedies, Lord Melchett hands Blackadder a map and says, “Farewell, Blackadder. The foremost cartographers of the land have prepared this for you; it ’s a map of the area that you ’ll be traversing.” When Blackadder opens it, he sees the map is blank. Lord Melchett smiles and adds, “They ’ll be very grateful if you could just fi ll it in as you go along. Bye-bye.”

Luckily, you do not need to be without a map, or indeed to fi ll in an empty map as you go along. Code Red will show you how to navi-gate the treacherous currents ahead.

Key Lessons from the Chapter

In this chapter we learned:

• Before the Great Financial Crisis, central bankers used conven-tional monetary policy. Now they are experimenting with noncon-ventional “Code Red” policies like quantitative easing, zero interest rates, large-scale asset purchases, and currency debasement. These policies will lead to infl ation in the long run.

• If you have borrowed too much, it is good to spend less and save. Central bankers, however, want everyone to keep borrowing and spending. Their policies are designed to encourage borrowing and speculation.

• The way to get people to spend their money instead of save is to create negative real interest rates on cash. Infl ation in most coun-tries is higher than interest rates, so cash is trash.

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• Politicians and central bankers want to encourage exports, so they are trying to devalue their currencies and make goods and services cheaper for foreigners. Unfortunately, not everyone can devalue their currency at the same time.

• Currency wars have happened before in the 1930s and 1970s. They rarely end well for anyone, but governments pursue currency wars anyway.

• Let ’s review some Code Red terms:• ZIRPs—zero interest rate policies. Many central banks have cut

interest rates to zero and can ’t cut them anymore. The central banks have promised to keep them near zero for years.

• LSAP—large-scale asset purchase program. This is when a central bank prints money to buy bonds, mortgage securities or stocks.

• QE—quantitative easing. This is when central banks expand the size of their balance sheet to infl uence the economy rather than through raising or lowering interest rates.

• Currency wars—is a policy to deliberately weaken your own currency. This happens when central banks use QE and ZIRP to reduce the attractiveness of holding cash. Central banks also can “talk down” their currency and say they want it to go lower.

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7

Chapter 2

Revelation (Five Minutes to Midnight)

A ngela Merkel stepped out of her Audi A8 and on to the red car-pet at the Cannes conference center to be greeted by Nicolas Sarkozy fl anked by French Republican Guards in white

breeches and ceremonial plumed helmets, their sabres held aloft in salute. For all the pomp, the mood on the French Riviera in November 2011 was far from celebratory: Merkel shook her head and Sarkozy raised his hands in a gesture of exasperation as they met. It was Greece again.

Europe was two years into the sovereign debt crisis that had emerged in Greece and was rippling through the euro area. Governments were toppling as borrowing costs soared, dividing the region into a relatively healthy northern core anchored by Germany and a weaker periph-ery that ran in an arc from Ireland to Spain and Portugal, through Italy to its focal point, Greece. Each step of the fi ght to beat back the con-tagion only ever calmed fi nancial markets for a matter of weeks or less before the fl ames reappeared somewhere else. Two bailouts worth 240 billion euros for Greece alone, almost the equivalent of its entire annual gross domestic product, the promise of debt relief, enrolling the expertise of the International Monetary Fund (IMF) alongside a 440 billion euro European rescue fund had failed to stop the crisis in its tracks. Now Greece ’s Prime Minister George Papandreou had given

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8 a n g e l a m e r k e l

a televised address in Athens announcing his intention to hold a ref-erendum on the latest round of measures approved by European gov-ernments to aid his country. A “No” vote would unravel what progress had been made and cause fresh waves of uncertainty to crash over the euro area, throwing the future of the single currency further into doubt. Merkel, as the leader of Europe ’s dominant economy, was fi rst in line to stop that from happening.

She and Sarkozy met in Cannes on the eve of a Group of 20 sum-mit of world leaders to decide the next move in their campaign to save the euro and defend European unity. Over two days in the Cannes con-ference center at one end of the palm-lined Boulevard de la Croisette, Merkel joined with Sarkozy to threaten Greece with defenestration from the euro and browbeat Italian Prime Minister Silvio Berlusconi into the humiliation of allowing outside monitoring of his country ’s economy. Within a week of being publicly cut loose, the Greek and Italian lead-ers lost what residual support they had and stood down, twin victims of the crisis. It was regime change by alternative means. Cannes, the Riviera town that hosts the eponymous fi lm festival, was the moment that all strands came together in the crisis, and Merkel was the principal actor.

The Greek economy was on a life support system, dependent upon international aid as it faced a fi fth straight year of recession. Public back-ing for Papandreou ’s government had collapsed as jobs and spending were slashed in a bid to wrestle down the biggest debt load per cap-ita in the 27-nation European Union, 1 measures that were demanded in return for fi nancial help under the terms of Greece ’s rescue deal. Papandreou ’s way out was to call a referendum in a bid to lance the boil and win some space to press on in the hope that signs of progress would emerge to alleviate the anger at home. His problem was that he failed to inform either his European partners or his own ministers before he made the announcement. “His behavior was disloyal,” said Luxembourg ’s Prime Minister Jean-Claude Juncker, who also headed meetings of fi nance ministers of the euro countries, a role that gained in impor-tance the longer the crisis persisted. “We would like to have been told.” 2 Le Monde reported that Sarkozy was dismayed by the revelation. The G-20 summit hosted by France was meant to set the stage for his cam-paign for a second term. Sarkozy planned to show a united European

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Revelation (Five Minutes to Midnight) 9

front and win agreement from world leaders for a global eff ort to restore confi dence to fi nancial markets that were losing faith in Europe ’s ability to tackle the malaise at its heart. He was going to be photographed with Chinese President Hu Jintao and sign autographs with U.S. President Barack Obama as the crowds cheered. “History is being written in Cannes,” read the G-20 banners going up around the town. Now his plans were threatened by Greece, and it wasn ’t even a member of the G-20 club.

In Berlin, Chancellor Merkel learned of the referendum at 7:20 p.m. on October 31 and took a moment to consider her response. She called Sarkozy and the two decided to summon Papandreou to Cannes to explain himself. They also agreed to halt the next aid payment to Greece until the referendum was cleared up, money that Greece des-perately needed to pay its bills. At 7:15 a.m. on Tuesday morning, German Finance Minister Wolfgang Schäuble called his Greek coun-terpart, Evangelos Venizelos, in the Athens hospital where he was undergoing treatment for stomach pains and told him of the deci-sion. Finance ministers from the other euro countries rubber stamped the suspension of aid within 90 minutes. Greece was eff ectively in limbo until Merkel and Sarkozy decided what to do with Papandreou. “Merkel and Sarkozy were upset because they felt they were betrayed,” said Xavier Musca, Sarkozy ’s chief economic adviser and G-20 coordi-nator at the time. “They also felt Papandreou was not reliable, because they had spent one night with him discussing everything, and then he decides to do something he never talked about.” 3

The night in question was a 10-hour crisis session of European leaders in Brussels the previous week on October 26–27 again domi-nated by Greece. Papandreou ’s maneuvering was particularly galling for Merkel and Sarkozy because they had sat up half the night to nego-tiate a deal aimed at saving Greece, the second in almost 18 months. Their backing had secured agreement on a 130 billion-euro bailout for Greece crafted with the IMF on top of a 110 billion-euro rescue agreed in May 2010. They had personally intervened with the banks ’ representative, Charles Dallara of the International Institute of Finance, summoning him from his hotel that night to accept losses of 50 percent on Greek government debt held in private hands. When he resisted, he was told the alternative was to allow Greece to go bankrupt, after

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which the banks would in all likelihood receive nothing back on their investments. 4 The same summit also forged a plan to increase Europe ’s rescue fund for any future countries that went the way of Greece to 1 trillion euros, as well as compelling banks to raise the amount of money they held in store to absorb fi nancial shocks. Taken together, it was a package that promised to fi nally snuff out the fl ames of fi nancial contagion that were spreading across Europe while putting a lid on the source of the confl agration: Greece. At the summit ’s close, Papandreou personally thanked Merkel and Sarkozy for their eff orts. “This agree-ment gives us time,” he said. “Tens of billions of euros have been lifted from the backs of the Greek people.” Even Merkel departed from her characteristically restrained rhetoric. “I am very aware that the world ’s attention was on these talks,” she said at a press conference after 4 a.m. as the summit ended. “We Europeans showed tonight that we reached the right conclusions.” It took one weekend for Europe to demonstrate its inherent capacity to shoot itself in the foot. Greeks were in open rebellion and opposed putting their country any more at the mercy of its international creditors. They wanted nothing do with a policy that promised to infl ict yet more deprivation on a population already on its knees. Papandreou, having successfully negotiated for the debt burden to be eased, returned home to be greeted as a traitor.

A snap poll in Greece taken after the EU summit fl oated the idea that the measures agreed should be put to a referendum, with 46 per-cent saying they would vote against. More than seven in 10 still said they wanted to stay in the euro. With his majority whittled down to 153 seats in the 300-member parliament, Papandreou felt he needed to resolve that contradiction and regain democratic legitimacy. A plebi-scite fi t the bill, even if for Greece as well as for the rest of Europe the prospect of a referendum created a whole new set of unknown factors. International fi nancial markets, already highly strung after months of bombardment by the crisis centered on Greece, were quick to off er their verdict. On Tuesday, November 1, the day after the referendum plan was announced, Germany ’s DAX lost 5 percent, France ’s CAC 40 Index dropped 5.4 percent and Italy ’s FTSE MIB Index sank 6.8 per-cent. U.S. stocks were hit and shares in Asia tumbled. National Bank of Greece plunged 15 percent, sending its share price to its lowest since 1992. 5 Fitch Ratings said the referendum “dramatically raises the stakes

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for Greece and the eurozone,” increasing the risks of a “forced and disorderly” default. What that meant for the rest of the eurozone was incalculable, but the implications were dire. According to an estimate by Natixis, if Greece left the euro it could cause an additional 16.4 bil-lion euros in net losses to French banks alone, with Sarkozy ’s govern-ment left to fi ll the hole. 6

Papandreou ’s proposal “surprised all of Europe,” the French presi-dent said on November 1. “The plan adopted unanimously by the 17 members of the euro area last Thursday is the only possible way to resolve the problem of Greek debt.” In a joint statement issued the same day, he and Merkel said the package of measures agreed in Brussels was “more necessary than ever today.” EU President Herman Van Rompuy and EU Commission President José Barroso raised the pressure on Papandreou to stop the deal from unraveling. “We fully trust that Greece will honor the commitments undertaken in relations to the euro area and the international community,” they said. Italy, the euro area ’s third largest economy, was meanwhile coming under threat. That night in Rome, on the eve of the G-20 summit and after a day in which Italy ’s government borrowing costs climbed to the highest rela-tive to Germany since before the advent of the euro, Prime Minister Berlusconi called an emergency meeting of his Cabinet.

With the stage set for Cannes, Merkel and Sarkozy arranged to meet Papandreou at the fi lm festival center facing the harbor fi lled with extravagant super-yachts. The Greek premier arrived a few hours after Merkel. This time there was no guard of honor. The EU ’s Barroso and Van Rompuy attended the November 2 meeting along with the euro-group head Juncker, IMF chief Christine Lagarde and the fi nance min-isters of France, Germany and Greece. Papandreou arrived in Cannes bolstered by his Cabinet ’s unanimous endorsement for his referendum plan, for all the residual doubts. There was still no word on the question to be put to the people. “The referendum will be a clear mandate and strong message within and outside Greece on our European course and our participation in the euro,” Papandreou told his ministers that morning before leaving for France. Already having to fend off calls for new elections from the opposition New Democracy party led by Antonis Samaras, the Greek premier said the question was not one of his

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government or another government: “The dilemma is yes or no to the loan accord, yes or no to Europe, yes or no to the euro.”

Merkel and Sarkozy wouldn ’t allow Papandreou the luxury of choice. The meeting, in one of the many rooms off the main confer-ence hall, was explosive. Merkel, who was visibly “very upset,” accord-ing to Musca, saw it as time to face up to some unpleasant truths that had been avoided for too long. She and Sarkozy confronted Papandreou and berated him for presenting them with a fait accompli. Yes, the Greek people had made sacrifi ces, but the country as a whole was not an innocent party in the crisis of confi dence sweeping the eurozone. They told him his planned ballot had placed the entire euro area at risk, and Europe ’s biggest powers could not let the single cur-rency be wrecked by one country. Suspecting him of trying to wrig-gle out of the commitments he made one week previously in Brussels, they handed him an ultimatum: hold to the agreement or wave good-bye to 8 billion euros in international rescue funds he needed to pay Greece ’s bills. If he must hold a referendum on the outcome of what was decided, then it could be about one thing only: Greece ’s future membership of the euro; in or out, they were prepared to let Greece go and risk the consequences. Sarkozy and Merkel dictated the tim-ing and the content of Papandreou ’s referendum, and spelled out the consequences of its outcome. The vote had to be brought forward to December to get it out of the way, removing a source of uncertainty as soon as possible. It could address Greece ’s future in the euro only and not any aspect of the country ’s bailout terms. Furthermore, there would be no money for Greece until the result was known. Sarkozy held a press conference after the meeting and said that not one cent would fl ow to Greece in the event of a “No” vote. It was all or noth-ing. Papandreou, presented with no alternative and his referendum eviscerated, accepted their terms. Publicly humiliated, he returned to Athens to face a confi dence vote in parliament.

The G-20 started the next day, Thursday November 3, with a discus-sion of Greece. Underscoring the global ramifi cations of one small coun-try ’s travails, a television set was brought into the main meeting room to allow leaders to watch the debate in the Greek parliament broad-cast live on BBC World. As he addressed the main chamber in Athens, world leaders and the assembled press of more than 20 nations gathered

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around television screens to watch Papandreou. His majority dwin-dling further to two, the prime minister made a plea for a government of national unity to overcome the country ’s epic problems. Political consensus, with the opposition coming on board to secure out-side aid and help the transition through this unprecedented situation, would remove the need to ask the public ’s backing for the deal struck in Brussels, he said. Venizelos, his fi nance minister, was more direct: Greece wasn ’t going to hold a referendum. The vote scrapped and his attempt to seek legitimacy for the deal in tatters, Papandreou off ered to stand aside to help the formation of a national unity government. He went on to win the confi dence ballot by 153 votes to 145 votes after promising his own parliamentary group that he would go. His last-ditch gamble had failed. Politically he was a spent force and he resigned the following week on November 11, nine days after Merkel and Sarkozy lost patience with him. Papandreou, who compared Greece ’s path out of the crisis to Homer ’s classic tale of Odysseus ’s 10-year jour-ney back to Ithaca, foundered at sea without reaching home. Merkel, acting with Sarkozy, helped seal his fate.

If Greece could trigger the biggest two-day decline in global stocks in almost three years, as Papandreou ’s referendum fl ip-fl op had done, then events in Italy had the potential to cause even more carnage. Italy, the third biggest economy in the euro, with domestic output almost 10 times that of Greece, was becoming a worry to Merkel and Sarkozy alike. They ’d already confronted Berlusconi on October 23 at a previ-ous EU summit and told him to follow through on his commitments. Asked at a joint press conference what they ’d said to Berlusconi then, Merkel and Sarkozy looked at each other for a moment, then laughed. Trust can only be regained by Italy assuming its responsibilities and taking credible steps for the future, Merkel said, dictating to Berlusconi what must be done. “Italy has great strengths but Italy also has a very high overall debt level, and that has to be credibly reduced,” she said. “That, I think, is the expectation on Italy.” 7 On the eve of traveling to Cannes, with Italian government borrowing costs soaring, Berlusconi had promised to enact emergency measures in a budget bill to be passed that month including raising the retirement age, easing rules on fi ring workers, and accelerating state asset sales. Yet having given the

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wrong signals to markets in the past, Berlusconi was unable to give investors the assurances they wanted on Italy ’s policy direction to merit an easing of the government ’s costs of borrowing. Germany and France were pressing the Italians in private to announce budget-ary measures before it was too late. Powerless to change his course and unable to have him fail to meet his commitments, the French and German leaders summoned Berlusconi to a room in the conference center on Thursday morning. As with Papandreou, they gave him an ultimatum: this was not a discussion about voluntary measures. Sarkozy and Merkel told Berlusconi that solving Greece was one thing, deal-ing with Italy a problem of a diff erent magnitude. Unless he gave an immediate signal demonstrating that he was aware of the gravity of the situation, he was lost. Now that the fi re of contagion was in Italy, the whole eurozone was at risk of implosion, they said: Do something about it. When Berlusconi said that he had always done the right thing by Italy, Merkel and Sarkozy told him markets didn ’t share that faith. He needed to do something quickly to regain market confi dence if he was to give Italy a chance of surviving the crisis. Boxed in, Berlusconi agreed to have the IMF send outside monitors to assess Italy ’s budget. In a statement issued the following day at the close of the G-20, Christine Lagarde welcomed “Italy ’s decision to invite the IMF to intensify our surveillance and monitoring work, to help support the major steps being taken by the government on both fi scal adjust-ment and structural reforms.” It was too little too late. Battered by the markets that drove Italy ’s borrowing costs to fresh records, Berlusconi announced his resignation on November 10.

For Merkel, whose position as Europe ’s principal decision maker was cemented six months later when she lost her ally Sarkozy in France ’s presidential election, the moment of truth for the euro area was the latest incarnation of fi nancial crisis that had rocked her chancellor-ship almost since the beginning. Merkel was just 18 months into offi ce when she was confronted with the worst global fi nancial meltdown in living memory. She set about resolving each stage of crisis for which there was no playbook – in the banks, the economy, and as a result of euro countries ’ debt loads – and she learned along the way. Catapulted to the forefront of European policy making during the euro trauma,

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it came to defi ne Merkel ’s chancellorship even as she struggled for a solution. Some leaders, like Papandreou and Berlusconi, collapse and fall victim to crisis; others like Merkel fl ourish. Lambasted for delay-ing, for backtracking, and for refusing to commit more resources to the crisis fi ght, Merkel showed at Cannes that she can suddenly be decisive, brutally so.

The source of her resoluteness lay four months previously in the summer of 2011. Markets were plunging globally with the realiza-tion that Europe ’s common eff orts to help Greece had failed and the bailout program wasn ’t working, spelling trouble for the rest of the euro area. An EU summit on July 21 had agreed on the second Greek bailout of 130 billion euros among a package of steps that included expanding the powers of the European rescue fund and easing the terms of emergency bailout loans awarded to Portugal and Ireland. Merkel also quietly dropped plans to enlist banks and other investors in helping to pay for the fallout of crises once a permanent rescue fund was set up in 2013, after criticism from the European Central Bank (ECB) and the U.S. that forcing the private sector to accept losses on their investments would worsen the situation and could tip the euro area over the edge. However, the summit still backed a German-led push for a restructuring of Greek debt, without shoring up Spain and Italy against contagion, sowing the seeds of the next bout of trouble. As early as April 2011, Germany had signaled its willingness to impose losses on Greece bondholders in the face of pledges by Papandreou to avoid such a situation. Werner Hoyer, Germany ’s minister for European aff airs, said that a so-called haircut on the debt held by investors “would not be a disaster.” 8 By broaching a previously taboo subject, Germany was setting itself up for a widening of the crisis for politi-cal reasons. The market response was swift: the turmoil spread and started to infect core euro countries, with the interest rates paid by the Spanish, Italian, and even French governments climbing steeply. ECB President Jean-Claude Trichet instructed the central bank to step in and start buying Spanish and Italian government bonds in a bid to impose some calm and stop the situation from spiraling out of control.

Until that summer, Europe ’s leaders had focused on tackling small, peripheral countries: Greece, Ireland and Portugal, together worth some 6 percent of euro area gross domestic product (GDP). The

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meltdown showed the crisis had moved to the core, marauding Italy and Spain, jointly representing more than 25 percent of the euro area ’s output, and lapping at the doors of the region ’s linchpin, Germany. Forced to confront the evidence that the entire region was facing an existential threat, Merkel shifted her focus: she decided she had to save the euro and to take Europe with her. As early as May 2010, she had expressed her conviction that “our Europe will overcome the present crisis of our common currency.” Now it was time to act. Up to that point, Merkel insisted there were no innocent victims of the crisis, that countries had brought the market reaction upon themselves, whether through greed, corruption, or ineptitude. As Italy was sucked into the maelstrom despite a budget defi cit of 3.9 percent in 2011 – just 0.9 percentage points outside EU limits and lower than France ’s 9 – she had to question that assessment. Markets were starting to price in a 98 percent chance of a Greek default, yet Merkel concluded it was impos-sible to calculate the impact of a “disorderly insolvency” on the wider euro area. Merkel told a closed meeting of leaders of her parliamen-tary group as they gathered in the Reichstag on the last day of August after the summer break that she would not go down in history as the person who wrecked the euro. 10 With a lack of drama typical of the chancellor, she announced her decision to the world two weeks later on a regional radio station serving the greater Berlin area. “The top prior-ity is to avoid an uncontrolled insolvency because that wouldn ’t just hit Greece,” Merkel said in an rbb Inforadio interview on September 13. “Everything must be done to keep the euro area together politically, because we would very quickly face a domino eff ect” otherwise. 11

The U.S. was quick to recognize the shift in Merkel ’s thinking as a turning point for the global economy. Treasury Secretary Timothy Geithner appeared on CNBC the following day and praised Merkel ’s comments as an acknowledgment that Europe ’s crisis response to date had been “behind the curve” and that more had to be done. “And I think it ’s important that you saw the Chancellor of Germany say yes-terday – Angela Merkel say yesterday they are absolutely committed, and they have the fi nancial capacity and the economic capacity to do what it takes to hold this thing together,” Geithner said. 12

Merkel had until then been prepared to make it easy for Greece to leave the euro, perhaps off ering guarantees of an early return to the

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currency under certain conditions, but the decision had to come from Greece. There was no mechanism to expel a country, however way-ward, and to do so without the Greek government ’s agreement would have spelled meltdown. With the realization that this was a place she could not go, Merkel swung behind Greece. Gone was the chastising language threatening sanctions on defi cit “sinners” and in its place was encouragement to meet targets on the road to recovery. “We want a strong Greece in the euro area and Germany is ready to off er all kinds of help that is needed,” Merkel said after meeting with Papandreou in Berlin two weeks later, on September 27, 2011. Having fi nally acknowledged the stakes, Merkel made a choice to hold the euro-zone together. That was why Papandreou ’s referendum so incensed her. It also explained Merkel ’s reconciliation with his successor, Antonis Samaras, after snubbing him for more than a year and a half. As the fall of 2011 drew closer, she had to rebalance German interests against Europe ’s future, pitting her domestic reality against the wider eff ort to save Europe ’s postwar unity. For a chancellor known for her love of weighing the evidence before settling upon her preferred option, it was decision time.

French philosopher Bernard-Henri Lévy, interviewed in the German newspaper Frankfurter Allgemeine Zeitung in November 2012, said the fact that Greece and Italy – the cradles of European civilization – were among the countries worst aff ected by the crisis showed how it had reached “to the very fundament of European existence.” The cri-sis had overcome Europe ’s “memory, everything that makes up its basis and origins, its soul, its grammar,” he said. 13 Lévy ’s assessment of the debt crisis was dramatic. Yet the fact he pronounced on it at all under-scored the extent to which the saga of Greece and its sequels had gone mainstream. As the impact began to be felt by every taxpayer, it went from back page business news to the front pages of the tabloids. The lexicon of the crisis began to seep into the popular culture, with bond yields and spreads used to denote how bad things were. Dispatches from Greece or details of the latest EU summit agreement were top-of-the-hour news across Europe, raising the pressure on Merkel, who was cast as making or breaking deals. If the chancellor glanced at Bild , Germany ’s biggest-selling daily, she saw headlines such as “So the

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Greeks DO want our money,” or “The Iron Chancellor,” an epithet fi rst attached to Bismarck, the fi rst chancellor of a united Germany. Bild regularly featured the crisis on its front page alongside pictures of topless women, criticizing Greece or railing against joint sales of government bonds across the euro region – a proposal known as euro bonds that would mean Germany underwriting the debts of weaker states.

While Germany obsessed about how much it was having to pay for euro rescues, others were preoccupied with how much their gov-ernments were paying to service debts. The higher the rate charged by markets, the riskier lending to the government was seen to be. Greece, Portugal, and Ireland were unable to keep functioning as their respec-tive costs breached 7 percent, forcing them to seek outside help. The spread, or divergence from the German bonds that serve as the bench-mark, showed how far from the path of fi scal rectitude a country had strayed. In France, “les spreads” became a national obsession; in Italy they echoed political turmoil that helped bring down governments. Italy ’s top-selling Corriere della Sera ran a headline on its front page on November 9, 2011, proclaiming “Spread a 500,” as the spread over Germany reached 500 basis points, or 5 percentage points. 14 Berlusconi announced his intention to step down as premier the next day. Pope Benedict XVI, a German, used one of his fi nal speeches as pontiff , at the Vatican in January 2013, to urge European leaders to devote the same energy to tackling the growing divergence in wealth as the spread in borrowing costs.

With euro countries locked into a single exchange rate, the hith-erto obscure business of buying and selling government bonds became both an indicator of the relative economic performance of the 17 countries belonging to the euro and a sign of how imbalanced mar-ket perceptions of them had become. Merkel ’s response was to call for all euro countries to undertake measures aimed at reducing debt and making Europe more economically competitive; though she never said it in such plain terms, they should become a lot more like Germany.

With Europe split into those countries in need of help and those in a position to provide it, Merkel ’s combination of austerity and struc-tural reforms gained Germany enemies as the economic mood dark-ened. Economists such as Nobel Prize winner Paul Krugman held

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Germany to blame for exacerbating the crisis by enforcing budget cuts at a time of recession. In his New York Times blog, Krugman compared the process to the medieval practice of bleeding a patient to make them well. Billionaire investor George Soros said Merkel risked gen-erating a revolt across Europe. The Obama administration clashed with Merkel over her refusal to deploy Germany ’s economic might to do more to stop the crisis from proliferating. Europeans haven ’t responded “as eff ectively as they needed to,” Obama said during a roundtable dis-cussion at the White House on September 28, 2011. U.S. offi cials have been more scathing in private, applying constant pressure for Germany to take the lead and calm the crisis, just as they badgered Germany to step up domestic consumption and increase the size of its economic stimulus measures in 2009. They acknowledge that Merkel has been pivotal throughout, however. One senior U.S. offi cial said that Merkel has been the key decision maker at all turning points in the crisis.

What anyone attempting to coerce Merkel into more action had to learn to appreciate was the domestic balancing act she had to per-form, not only between the public and her three-party coalition, but also taking into account the responses of Germany ’s constitutional court and the powerful voice of the central bank, the Bundesbank. The day after Obama ’s public comment on the inadequacy of Europe ’s cri-sis response, Merkel faced down her coalition critics to win passage in the lower house, the Bundestag, of a bill allowing an expansion of the euro area rescue fund ’s fi repower, raising Germany ’s share of guarantees to a maximum 211 billion euros from 123 billion euros. She had paved the way for it the previous month by allowing the German parlia-ment veto right over future rescue measures, thus satisfying potential rebels as well as settling any legal doubts of the constitutional court in Karlsruhe. She also used the opportunity to stamp her authority on the coalition, telling dissenters to stop talking down Greece. “What we don ’t need is unrest in the fi nancial markets,” she said. “The uncertain-ties are big enough as it is.” But the domestic concerns remained.

The raising of Germany ’s guarantees meant that Merkel was unable to agree to a Sarkozy proposal at Cannes to enlist the rest of the world to help Europe ’s crisis-fi ghting eff orts. The French had brokered a tenta-tive deal with G-20 nations including China and the U.K. to provide funds that would enable the euro rescue fund to be leveraged to increase

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its size. To go along, Merkel had to win the support of the Bundesbank. Although by then run by Merkel ’s former chief economic adviser, Jens Weidmann, the German central bank refused. The French suggested using a credit from the state-owned KfW development bank, but that too was out of the question as parliament would have to vote on any attempt to use the KfW. Coming so soon after lawmakers agreed to raise German liabilities to 211 billion euros, that route too was politically impossible. The French plan was thwarted by Merkel ’s unwillingness to risk a domestic defeat and it came to nothing. Where outside observ-ers saw German obstructionism during the crisis, Merkel ’s govern-ment saw the pressure placed on them to agree to measures that were domestically impossible as posing a threat to the most stable economy in Europe. Political instability in Germany would not help the crisis fi ght, in the Merkel administration ’s view. Nevertheless, as the turmoil spread, Europe ’s epiphany was overdue and it fell to Merkel, the pastor ’s daugh-ter from the provincial East German town of Templin, to act.

Notes

1. European Commission Autumn projections, November 7, 2012: http://ec.europa.eu/economy_fi nance/eu/forecasts/2012_autumn_forecast_en.htm .

2. Juncker interview with Germany ’s ZDF television, November 3, 2011, on Luxembourg government website: http://www.gouvernement.lu/salle_presse/interviews/2011/11-novembre/03-pm/index.html .

3. Interview in Paris, November 30, 2012. 4. “Sarkozy Temper Boils, Banks Yield in Six-Day War Saving the Euro,”

Bloomberg News , November 2, 2011: http://www.businessweek.com/news/2011–11–02/sarkozy-temper-boils-banks-yield-in-six-day-war-saving-the-euro.html .

5. “Papandreou Grip on Power Weakens,” Bloomberg News , November 14, 2011: http://www.businessweek.com/news/2011–11–14/papandreou-grip-on-power-weakens-as-lawmakers-rebel-on-vote.html .

6. James Amott, “Agricole May Lose EU10.4b on Greek Euro Exit, Natixis Says,” Bloomberg News , November 2, 2011: (not on web).

7. Merkel–Sarkozy press conference: https://www.youtube.com/watch?v=D8NtEXnc4jY .

8. “Germany Would Back Greece Debt Restructuring, Hoyer Says,” Bloomberg News , April 15, 2011: http://www.bloomberg.com/news/2011–04–15/ger many-would-back-greece-if-it-sought-debt-restructuring-minister-says.html .

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9. Kristian Siedenberg, “EU commission autumn forecasts,” Bloomberg table. 10. “Angela Merkel: A Rational European,” Frankfurter Allgemeine Zeitung ,

October 13, 2012: http://www.faz.net/aktuell/politik/europaeische-union/angela-merkel-europaeerin-aus-vernunft-11924570.html .

11. rbb Inforadio interview, September 13, 2011: http://www.bundeskanzlerin.de/Content/DE/Artikel/2011/09/2011–09–13-merkel-rbb-euro.html .

12. Transcript of Geithner interview with CNBC ’s Jim Cramer: http://www.cnbc.com/id/44487020/ .

13. Frankfurter Allgemeine Zeitung , November 20, 2012: http://www.faz.net/aktuell/feuilleton/debatten/bernard-henri-levy-im-gespraech-reformen-reichen-nicht-aus-um-europa-zu-retten-11965397.html .

14. Dan Liefgreen and Armorel Kenna, “Italians Obsessed by ‘Lo Spread’ as Advance in Bond Yields Makes Headlines,” Bloomberg News , November 14, 2011: http://www.bloomberg.com/news/2011–11–14/italians-obsessed-by-lo-spread-as-advance-in-bond-yields-makes-headlines.html .

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A Five-Sigma Event THE WORLD ’S GREATEST INVESTOR

Brace yourself,” Buffett said, with a sly grin. He was sitting in a Manhattan living room on a spring morning with one of his dear-est and oldest friends, Carol Loomis. A New York Times best-selling author and an award-winning journalist, Carol is senior editor-at-large at Fortune magazine, where she has worked since 1954, and is considered to be the magazine ’s resident expert on Warren Buffett. It is well known among the Buffett faithful that she has also been editing Berkshire Hathaway ’s annual reports since 1977.

On that spring day in 2006, Buffett told Carol that he had changed his thinking about how and when he was going to give away his fortune in Berkshire Hathaway stock. Like most people, Carol knew that Buffett, after a small allocation to his three chil-dren, was going to leave 99 percent of his wealth to charity, but it was always thought it would go to the Buffett Foundation estab-lished by his late wife, Susan. Now he was telling Carol he had changed his mind. “I know what I want to do,” he said, “and it makes sense to get going.” 1

So, shortly before lunch, on June 26, 2006, Warren Buffett, who was then the second richest man in the world, stepped up to the microphone inside the New York Public Library. The audience—hundreds of the wealthiest people in the city—greeted him with a standing ovation. After a few brief words, Buffett reached inside his

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2 The Warren Buffett Way

jacket pocket and pulled out fi ve letters. Each one announced the disposition of his fortune, and only awaited his signature. The fi rst three letters were easy; he just signed “Dad” and then handed them to his children: daughter Suze, eldest son Howard, and second son Peter. The fourth letter was turned over to a representative of his late wife ’s charitable foundation. Together, these four letters prom-ised to give away a combined $6 billion. 2

The fi fth letter was the surprise. Buffett signed it and handed it to the wife of the only man on the planet who was richer than him-self, Bill Gates. With that last letter, Buffett pledged over $30 billion in Berkshire Hathaway stock to the world ’s largest philanthropic organization, the Bill and Melinda Gates Foundation. It was by far the single greatest amount of money ever given away, miles big-ger than the contributions by Andrew Carnegie ($7.2 billion when adjusted to current dollars), John D. Rockefeller ($7.1 billion), or John D. Rockefeller Jr. ($5.5 billion).

In the days that followed, there were countless questions. Was Buffett ill, perhaps even dying? “No, absolutely not,” he said. “I feel terrifi c.” Did his wife ’s passing have anything to do with his deci-sion? “Yes, it does,” confessed Buffett. It was well known that Susie would have inherited Buffett ’s fortune for the Buffett Foundation. “She would have enjoyed the process,” he said. “She was a little afraid of it, in terms of scaling up. But she would have liked doing it, and would have been very good at it.” 3

But after his wife ’s death, Buffett changed his thinking. He realized that the Bill and Melinda Gates Foundation was a terrifi c organization, already scaled to handle the billions of dollars Buffett was going to send its way. They “wouldn ’t have to go through the real grind of getting to a megasize like the Buffett Foundation would—and they could productively use my money now,” he said. “What can be more logical, in whatever you want done, than fi nd-ing someone better equipped than you are to do it?” 4

It was quintessential Buffett. Rationality prevailed. At Berkshire Hathaway, Buffett reminds us there are scores of managers run-ning businesses that do a much better job of running their opera-tions than he ever could. Likewise, the Bill and Melinda Gates

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A Five-Sigma Event 3

Foundation would do a better job of managing his philanthropy than he could do himself.

Bill Gates said of his friend, “Warren will be remembered not only as the greatest investor, but the world ’s greatest investor for good.” 5 This will most certainly be true. But it is important to remember that the good his philanthropic generosity will do was made possi-ble in the fi rst place by his unparalleled investing skill. When Buffett handed the letter and check for $30 billion to Melinda Gates, I immediately thought back to another check he had written 50 years earlier—for $100, his initial investment in the Buffett Partnership, Ltd.

Buffett has always claimed he won the ovarian lottery. He fi g-ures the odds of him being born in 1930 in the United States were about 30:1. He admits he couldn ’t run fast and would never have been a good football player. Neither, despite his talents at pluck-ing a ukulele, would he ever become a concert violinist. But he was “wired in a particular way” that would allow him “to thrive in a big capitalist economy with a lot of action.” 6

“My wealth has come from a combination of living in America, some lucky genes, and compound interest,” said Buffett. “My luck was accentuated by my living in a market system that sometimes produces distorted results, though overall it serves our country well.” To keep it all in perspective, Buffett humbly reminds us that he happens to work “in an economy that rewards someone who saves lives of others on a battlefi eld with a medal, rewards a great teacher with thank-you notes from parents, but rewards those who can detect the mispricing of securities with sums reaching into the billions.” He called it fate ’s capricious distribution of “long straws.” 7

That may be true. But in my mind, Buffett carved his own des-tiny, which determined his own fate—not the other way around. This is the story of how Warren Buffett made his own long straw.

Personal History and Investment Beginnings

Warren Edward Buffett was born August 30, 1930, in Omaha, Nebraska. He was the seventh generation of Buffetts to call Omaha home. The fi rst Nebraskan Buffett opened a grocery store in 1869.

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Buffett ’s grandfather also ran a grocery store and once employed a young Charlie Munger, the future vice chairman of Berkshire Hathaway. Buffett ’s father, Howard, was a local stockbroker and banker who later became a Republican Congressman.

It was said that as soon as Warren Buffett was born he was fasci-nated by numbers. That may be a stretch, but it is well documented that before he entered kindergarten he was already a calculating machine. As young boys, he and his best friend Bob Russell would sit on the Russell family porch recording license-plate numbers of the cars that passed by. When darkness fell, he and Bob would go inside, spread the Omaha World-Herald on the fl oor, and count the number of times each letter appeared in the paper. They then tallied their calculations in a scrapbook, as if it was top-secret information.

One of young Buffett ’s most prized toys came from his Aunt Alice, who was quite fond of her peculiar but immensely likable nephew and made him an irresistible offer: If he would agree to eat his asparagus, she would give him a stopwatch. Buffett was mes-merized by this precise counting machine and used it in endless little-boy ventures, like marble races. He would summon his two sisters into the bathroom, fi ll the tub with water, and then direct them to drop their marble into one end. The one whose marble reached the drain stopper fi rst was the winner (utilizing the tub ’s sloped shape). Buffett, stopwatch at the ready, timed and recorded each race.

But it was the second gift from Aunt Alice that sent six-year-old Buffett into a new direction—a fascination not with just num-bers, but with money. On Christmas day, Buffett ripped open his present and strapped onto his belt what would become his most treasured possession—a nickel-coated money changer. He quickly found many ways to put it to good use. He set up a table outside his house and sold Chiclets to anyone who passed by. He went door-to-door selling packs of gum and soda pop. He would by a six-pack of Coke at his grandfather ’s grocery store for 25 cents and sell the individual bottles for a nickel: 20 percent return on investment. He also sold, door-to-door, copies of the Saturday Evening Post and Liberty magazines. Each weekend he sold popcorn and peanuts at

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local football games. With him through all these enterprises was his money changer, taking in dollars and making change. 8

What now sounds like an idyllic childhood took an abrupt turn when Buffett ’s father returned home one night to inform the fam-ily the bank where he worked had closed. His job was gone and their savings were lost. The Great Depression had fi nally made its way to Omaha. Buffett ’s grandfather, the grocery store owner, gave Howard money to help support his family.

Fortunately, the sense of hopelessness did not last long. Howard Buffett soon pulled himself up and got back on his feet, announcing that Buffett, Sklenicka & Company had opened for business at the Union State building on Farnam Street, the same street where Buffett would someday buy a house and start his investment partnership.

The effect of the Great Depression, albeit brief, was hard on Buffett ’s family. It also made a deep and profound impression on young Warren. “He emerged from those fi rst hard years with an absolute drive to become very, very, very rich,” wrote Roger Lowenstein, author of Buffett: The Making of an American Capitalist . “He thought about it before he was fi ve years old. And from that time on, he scarcely stopped thinking about it.” 9

When Buffett turned 10, his father took him to New York. It was a birthday gift Howard gave to each of his children. “I told my Dad I wanted to see three things,” said Buffett. “I wanted to see the Scott Stamp and Coin Company. I wanted to see the Lionel Train Company. I wanted to see the New York Stock Exchange.” 10 After an overnight ride on the train, Buffett and his dad made their way to Wall Street, where they met with At Mol, a member of the exchange. “After lunch, a guy came along with a tray that had all these different kinds of tobacco leaves on it,” recalled Buffett. “He made up a cigar for Mr. Mol, who picked out the leaves he wanted. And I thought, this is it. It doesn ’t get any better than this. A custom-made cigar.” 11

Later, Howard Buffett introduced his son to Sidney Weinberg, a senior partner at Goldman Sachs, then considered the most famous man on Wall Street. Standing in Weinberg ’s offi ce, Buffett was mes-merized by the photographs and documents on the wall. He took note of the framed original letters, knowing full well they were

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written by famous people. While Howard and Sidney talked about fi nancial issues of the day, Buffett was oblivious, walking around and around Weinberg ’s offi ce staring at the artifacts. When it was time to go, Sidney Weinberg put his arm around Buffett and jok-ingly asked him what stock he liked. “He ’d forgotten it all the next day,” Buffett recalled, “but I remembered it forever.” 12

Even before Buffett traveled to New York, he was already intrigued with stocks and the stock market. He was a frequent visi-tor to his dad ’s brokerage offi ce, where he would stare at stock and bond certifi cates that hung on the wall, just like in Sidney Weinberg ’s offi ce. Often he would bounce down the two fl ights of stairs right into the Harris Upham brokerage fi rm. Many of the bro-kers became fond of the pesky kid who never seemed to stop ask-ing questions. From time to time they would allow young Warren to chalk the prices of stocks on the blackboard.

On Saturday mornings, when the stock exchange was open for two hours, Buffett would hang out with his paternal great-uncle Frank Buffett and his maternal great-uncle John Barber at the brokerage offi ce. According to Buffett, Uncle Frank was a perpet-ual bear and Uncle John was the ever-optimistic bull. Each com-peted for Buffett ’s attention with stories of how they thought the world would unfold. All the while, Buffett stared straight ahead at the Trans-Lux stock ticker, trying to make sense of the continu-ally changing stock prices. Each weekend he read the “Trader” column in Barron ’s . Once he fi nished reading all the books on his father ’s bookshelf, he consumed all the investment books at the local library. Soon he began charting stock prices himself, trying to understand the numerical patterns that were fl ashing by his eyes.

No one was surprised when 11-year-old Buffett announced he was ready to buy his fi rst shares of stock. However, they were shocked when he informed his family he wanted to invest $120, money he had saved from selling soda pop, peanuts, and maga-zines. He decided on Cities Service Preferred, one of his father ’s favorite stocks, and enticed his sister Doris to join him. They each bought three shares, for an investment of $114.75 each. Buffett had studied the price chart; he was confi dent.

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That summer the stock market declined, hitting its yearly low in June. The two junior Buffetts saw their stocks decline 30 percent. Not a day went by when Doris did not pester Warren about their loss, so when Cities Service Preferred recovered to $40 per share, he sold their holdings, for a $5 profi t.

To Buffett ’s chagrin, Cities Service Preferred soon soared to $202 a share. After commissions, Buffett calculated he had forgone a profi t of over $492. Since it had taken him fi ve years to save $120, he fi gured he had just given up 20 years of work. It was a painful lesson, but ultimately a valuable one. Buffett swore that, fi rst, he would never again be sidetracked by what he paid for the stock, and, second, he would not settle for small profi ts. At the wise age of 11, Buffett had already learned one of the most important lessons in investing—patience. (More about this crucial quality in Chapter 7.)

In 1942, when Buffett was 12, his father was elected to the U.S. Congress and moved the family to Washington. The change was hard on the young boy. Miserable and hopelessly homesick, he was allowed to return to Omaha for a year, to live with his grand-father and Aunt Alice. The following year, 1943, Warren gave Washington another chance.

With no friendly brokerage fi rms to hang out in, gradually Buffett ’s interest moved away from the stock market and toward entrepreneurial ventures. At age 13, he was working two paper routes, delivering the Washington Post and the Washington Times-Herald . At Woodrow Wilson High School, he made friends with Don Danly, who quickly became infected with Buffett ’s enthusiasm for making money. The two pooled their savings and bought reconditioned pin-ball machines for $25. Buffett convinced a local barber to let them put a machine in his shop for half the profi ts. After the fi rst day of operation, they returned to fi nd $4 in nickels in their very fi rst machine. The Wilson Coin-Operated Machine Company expanded to seven machines, and soon Buffett was taking home $50 per week.

By the time Buffett graduated from high school, his savings from various endeavors totaled $9,000. He promptly announced that he saw no reason to go to college, as it would interfere with his business ventures. His father overruled him, and by the fall

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Buffett found himself enrolled at the University of Pennsylvania ’s Wharton School of Business and Finance. Despite Wharton ’s emphasis on business and fi nance, Buffett was unimpressed with the university. “Not exactly turned on by it,” he confessed; “it didn ’t seem like I was learning a lot.” 13 The Wharton curriculum stressed the theoretical aspects of business; what interested Buffett were the practical aspects of a business—how to make money. After two years at Wharton (1947–1949), he transferred to the University of Nebraska. He took 14 courses in one year and graduated in 1950. He was not yet 20 years old.

Back in Omaha, Buffett reconnected with the stock market. He started collecting hot tips from brokers and subscribed to publish-ing services. He resurrected his price charts and studied books on technical analysis. He applied the McGee point-and-fi gure system and every other system he could think of, trying to fi gure out what would work. Then one day, browsing in the local library, he came across a recently published book titled The Intelligent Investor by Benjamin Graham. “That,” he said, “was like seeing the light.” 14

Graham ’s treatises on investing, including Security Analysis (1934), cowritten with David Dodd, so infl uenced Buffett that he left Omaha and traveled to New York to study with Graham at the Columbia University Graduate School of Business. Graham preached the importance of understanding a company ’s intrinsic value. He believed investors who accurately calculated this value and bought shares below it in price could be profi table in the market. This mathematical approach appealed to Buffett ’s love of numbers.

In Graham ’s class were 20 students. Many were older than Buffett and several were working on Wall Street. In the evening, these Wall Street professionals sat in Graham ’s class discussing which stocks were massively undervalued, and the next day they would be back at work buying the stocks analyzed the night before and making money.

It was soon clear to everyone that Buffett was the brightest stu-dent. He often raised his hand to answer Graham ’s question before Graham had fi nished asking it. Bill Ruane, who later cofounded

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the Sequoia Fund with Rick Cuniff, was in the same class. He recalls that there was an instantaneous chemistry between Graham and Buffett, and the rest of the class was primarily an audience. 15 Buffett ’s grade for the class was an A+—the fi rst A+ Graham had awarded in 22 years of teaching.

After graduating from Columbia, Buffett asked Graham for a job but was turned down. At fi rst he was stung by the rejection but later was told that the fi rm preferred to fi ll the slots at Graham-Newman with Jewish analysts who, it was perceived, were being treated unfairly on Wall Street. Undeterred, Buffett returned to Omaha, where he joined Buffett-Falk Company, his father ’s broker-age. He hit the ground running, eagerly recommending stocks that met Graham ’s value criteria. All the while Buffett stayed in touch with Graham, sending him stock ideas after stock ideas. Then, in 1954, Graham called with news: The religious barrier had been lifted and there was a seat at Graham-Newman if he was still inter-ested. Buffett was on the next plane to New York.

During his tenure at Graham-Newman, Buffett became fully immersed in his mentor ’s investment approach. In addition to Buffett, Graham also hired Walter Schloss, Tom Knapp, and Bill Ruane. Schloss went on to manage money at WJS Ltd. Partners for 28 years. Knapp, a Princeton chemistry major, was a founding partner in Tweedy, Browne Partners. Ruane cofounded the Sequoia Fund.

For Buffett, Graham was much more than a tutor. “It was Graham who provided the fi rst reliable map to that wondrous and often forbidding city, the stock market,” wrote Roger Lowenstein. “He laid out a methodological basis for picking stocks, previously a pseudoscience similar to gambling.” 16 Since the days when 11-year-old Buffett fi rst purchased Cities Service Preferred, he had spent half of his life studying the mysteries of the stock market. Now he had answers. Alice Schroeder, author of The Snowball: Warren Buffett and the Business of Life , wrote, “Warren ’s reaction was that of a man emerging from the cave in which he had been living all his life, blinking in the sunlight as he perceived reality for the fi rst time.” According to Schroeder, Buffett ’s original “concept of a stock was derived from the patterns formed by the prices at which pieces of

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paper were traded. Now he saw that those pieces of paper were sim-ply symbols of an underlying truth.” 17

In 1956, two years after Buffett arrived, Graham-Newman disbanded and Graham, then 61, decided to retire. Once again Buffett returned to Omaha. Armed with the knowledge he had acquired from Graham, and with the fi nancial backing of family and friends, he began a limited investment partnership. He was 25 years old.

The Buffett Partnership Ltd.

The Buffett Partnership began with seven limited partners who together contributed $105,000. Buffett, the general partner, started with $100. The limited partners received 6 percent annually on their investments and 75 percent of the profi ts above this bogey; Buffett earned the other 25 percent. But the goal of partnership was rela-tive, not absolute. Buffett ’s intention, he told his partners, was to beat the Dow Jones Industrial Average by 10 percentage points.

Buffett promised his partners that “our investments will be cho-sen on the basis of value not popularity” and that the partnership “will attempt to reduce permanently capital loss (not short-term quotational loss) to a minimum.” 18 Initially, the partnership bought undervalued common stocks based on Graham ’s strict criteria. In addition, Buffett also engaged in merger arbitrage—a strategy in which the stocks of two merging companies are simultaneously bought and sold to create a riskless profi t.

Out of the gate, the Buffett partnership posted incredible num-bers. In its fi rst fi ve years (1957–1961), a period in which the Dow was up 75 percent, the partnership gained 251 percent (181 per-cent for limited partners). Buffett was beating the Dow not by the promised 10 percentage points but by an average of 35.

As Buffett ’s reputation became more widely known, more peo-ple asked him to manage their money. As more investors came in, more partnerships were formed, until Buffett decided in 1962 to reorganize everything into a single partnership. That year Buffett moved the partnership offi ce from his home to Kiewit Plaza in

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Omaha, where his offi ce remains today. The following year, Buffett made one of his most famous investments, one that served to boost his already growing reputation.

One of the worst corporate scandals in the 1960s occurred when the Allied Crude Vegetable Oil Company, led by Tino De Angelis, discovered it could obtain loans based on the inventory of its salad oil. Using one simple fact—that oil fl oats on top of water—De Angelis rigged the game. He built a refi nery in New Jersey, put in 139 fi ve-story storage tanks to hold soybean oil, then fi lled the tanks with water topped with just a few feet of salad oil. When inspectors arrived to confi rm inventory, Allied employees would clamber up to the top of the tanks, dip in a measuring stick, and call out a false number to the inspectors on the ground. When the scandal broke, it was learned that Bank of America, Bank Leumi, American Express, and other international trading companies had backed over $150 million in fraudulent loans.

American Express was one of the biggest casualties of what became known as the salad oil scandal. The company lost $58 mil-lion and its share price dropped by over 50 percent. If Buffett had learned anything from Ben Graham, it was this: When a stock of a strong company sells below its intrinsic value, act decisively.

Buffett was aware of the $58 million loss, but what he did not know was how customers viewed the scandal. So he hung out at the cash registers of Omaha restaurants and discovered there was no drop-off in the use of the famous American Express Green Card. He also visited several banks in the area and learned that the fi nan-cial scandal was having no impact on the sale of American Express Travelers Cheques.

Returning to his offi ce, Buffett promptly invested $13 mil-lion—a whopping 25 percent of the partnership assets—in shares of American Express. Over the next two years, the shares tripled and the partners netted a cool $20 million in profi t. It was pure Graham, and pure Buffett.

In the beginning, Buffett confi ned the partnership to buying undervalued securities and certain merger arbitrage announce-ments. But in the fi fth year, he purchased his fi rst controlling interest

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in a business—the Dempster Mill Manufacturing Company, a maker of farm equipment. Next he began buying shares in an ailing New England textile company called Berkshire Hathaway, and by 1965 he had control of the business.

■ ■ ■

In differential calculus, an infl ection point is a point on a curve at which the curvature changes from being plus to minus or minus to plus. Infl ection points can also occur in companies, indus-tries, economies, geopolitical situations, and individuals as well. I believe the 1960s proved to be Buffett ’s infl ection point—where Buffett the investor evolved into Buffett the businessperson. It was also a period when the market itself reached an infl ection point. Since 1956, the valuation strategy outlined by Graham and used by Buffett had dominated the stock market. But by the mid-1960s a new era was unfolding. It was called the “Go-Go” years—the “Go-Go” referred to growth stocks. It was a time when greed begin driv-ing the market and where fast money was made and lost in the pursuit of high-fl ying performance stocks. 19

Despite the underlying shift in market psychology, the Buffett Partnership continued to post outstanding results. By the end of 1966, the partnership had gained 1,156 percent (704 percent for limited partners), blitzing the Dow, which was up 123 percent over the same period. Even so, Buffett was becoming increasingly uneasy. Whereas the market had been dancing to the principles outlined by Graham, the new music being played in the stock mar-ket made little sense to Buffett.

In 1969, Buffett decided to end the investment partnership. He found the market highly speculative and worthwhile values increas-ingly scarce. By the late 1960s, the stock market was dominated by highly priced growth stocks. The Nifty Fifty were on the tip of every investor ’s tongue. Stocks like Avon, Polaroid, and Xerox were trad-ing at fi fty to one hundred times earnings. Buffett mailed a letter to his partners confessing that he was out of step with the current market environment. “On one point, however, I am clear,” he said.

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“I will not abandon a previous approach whose logic I understand, although I fi nd it diffi cult to apply, even though it may mean forgo-ing large and apparently easy profi ts, to embrace an approach which I don ’t fully understand, have not practiced successfully and which possibly could lead to substantial permanent loss of capital.” 20

At the beginning of the partnership, Buffett had set a goal of outperforming the Dow by an average of 10 percentage points each year. Between 1957 and 1969, he did beat the Dow—not by 10 per-centage points a year but by 22! When the partnership disbanded, investors received their portions. Some were given an education in municipal bonds and others were directed to a money manager. The only individual whom Buffett recommended was Bill Ruane, his old classmate at Columbia. Ruane agreed to manage some of the partners ’ money, and thus was born the Sequoia Fund. Other members of the partnership, including Buffett, took their portions in Berkshire Hathaway stock. Buffett ’s share of the partnership had grown to $25 million, and that was enough to give him control of Berkshire Hathaway.

When Buffett disbanded the partnership, many thought the “money changer ’s” best days were behind him. In reality, he was just getting started.

Berkshire Hathaway

The original company, Berkshire Cotton Manufacturing, was incor-porated in 1889. Forty years later, Berkshire combined operations with several other textile mills, resulting in one of New England ’s largest industrial companies. During this period, Berkshire pro-duced approximately 25 percent of the country ’s cotton needs and absorbed 1 percent of New England ’s electrical capacity. In 1955, Berkshire merged with Hathaway Manufacturing, and the name was subsequently changed to Berkshire Hathaway.

Unfortunately, the years following the merger were dismal. In less than 10 years, stockholders ’ equity dropped by half and losses from operations exceeded $10 million. During the next 20 years, Buffett, along with Ken Chace, who managed the textile group,

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labored intensely to turn around the New England textile mills. Results were disappointing. Returns on equity struggled to reach double digits.

By the 1970s, shareholders of Berkshire Hathaway began to question the wisdom of retaining an investment in textiles. Buffett made no attempt to hide the diffi culties and on several occasions explained his thinking: The textile mills were the largest employer in the area; the workforce was an older age group that possessed relatively nontransferable skills; management had shown a high degree of enthusiasm; the unions were being reasonable; and, very importantly, Buffett believed that some profi ts could be realized from the textile business.

However, he made it clear that he expected the textile group to earn positive returns on modest capital expenditures. “I won ’t close down a business of subnormal profi tability merely to add a frac-tion of a point to our corporate returns,” said Buffett. “I also feel it is inappropriate for even an exceptionally profi table company to fund an operation once it appears to have unending losses in pros-pect. Adam Smith would disagree with my fi rst proposition and Karl Marx would disagree with my second; the middle ground,” he explained, “is the only position that leaves me comfortable.” 21

As Berkshire Hathaway entered the 1980s, Buffett was com-ing to grips with certain realities. First, the very nature of the tex-tile business made high returns on equity improbable. Textiles are commodities, and commodities by defi nition have a diffi cult time distinguishing their products from those of competitors. Foreign competition, employing a cheap labor force, was squeezing profi t margins. Second, in order to stay competitive the textile mills would require signifi cant capital improvements, a prospect that is frightening in an infl ationary environment and disastrous if the business returns are anemic.

Buffett was faced with a diffi cult choice. If he made large capital contributions to the textile division in order to remain competitive, Berkshire would be left with poor returns on what was becoming an expanding capital base. If he did not reinvest, Berkshire ’s tex-tile mills would become less competitive with other domestic textile

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manufacturers. Whether Berkshire reinvested or not, foreign com-petition continued to have an advantage by employing a cheaper labor force.

By 1980, the annual report revealed ominous clues for the future of the textile group. That year, the group lost its prestigious lead-off position in the Chairman ’s Letter. By the next year, the tex-tile group was not discussed in the letter at all. Then, the inevita-ble: In July 1985, Buffett closed the books on the textile group, thus ending a business that had begun some 100 years earlier.

Despite the misfortunes of the textile group, the experience was not a complete failure. First, Buffett learned a valuable lesson about corporate turnarounds: They seldom succeed. Second, the textile group did generate enough capital in the early years to buy an insurance company, and that is a much brighter story.

Insurance Operations

In March 1967, Berkshire Hathaway purchased, for $8.6 million, the outstanding stock of two insurance companies headquartered in Omaha: National Indemnity Company and National Fire & Marine Insurance Company. It was the beginning of Berkshire Hathaway ’s phenomenal success story.

To appreciate the phenomenon, it is important to recognize the true value of owning an insurance company. Insurance com-panies are sometimes good investments, sometimes not. They are, however, always terrifi c investment vehicles . Policyholders, in paying premiums, provide a constant stream of cash; insurance companies invest this cash until claims are fi led. Because of the uncertainty of when claims will occur, insurance companies opt to invest in liquid securities—primarily short-term fi xed income securities, longer-dated bonds, and stocks. Thus Warren Buffett acquired not only two modestly healthy companies, but also a cast-iron vehicle for managing investments.

In 1967, the two insurance companies had a bond portfolio worth more than $24.7 million and a stock portfolio worth $7.2 million. In two years, the combined portfolio approached $42 million. This was a

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handsome portfolio for a seasoned stock picker like Buffett. He had already experienced some limited success managing the textile com-pany ’s securities portfolio. When Buffett took control of Berkshire in 1965, the company had $2.9 million in marketable securities. By the end of the fi rst year Buffett had enlarged the securities account to $5.4 million. In 1967, the dollar return from investing was three times the return of the entire textile division, which had 10 times the equity base of the common stock portfolio.

It has been argued that when Buffett entered the insurance business and exited the textile business, he merely exchanged one commodity for another. Insurance companies, like textiles, are selling a product that is indistinguishable. Insurance policies are standardized and can be copied by anyone. There are no trademarks, patents, advantages in location, or raw materials that distinguish one from another. It is easy to get licensed, and insurance rates are an open book. Often the most distinguishable attribute of an insurance company is its personnel. The efforts of individual managers have enormous impact on an insurance company ’s performance. Over the years, Buffett has added several insurance companies to the Berkshire insurance group. One prominent addition, now well known thanks to a clever advertising campaign, is GEICO. By 1991, Berkshire Hathaway owned nearly half of GEICO ’s outstanding common shares. For the next three years, the company ’s impressive performance continued to climb; so did Buffett ’s interest. In 1994, Berkshire announced it owned 51 percent of the company, and serious discussion began on GEICO joining the Berkshire family. Two years later, Buffett wrote a check for $2.3 billion and GEICO became a wholly owned business.

Buffett was not done. In 1998, he paid seven times the amount he had spent to buy the remaining outstanding shares of GEICO—about $16 billion in Berkshire Hathaway stock—to acquire a rein-surance company called General Re. It was his biggest acquisition up to that date.

Over the years, Buffett has continued to buy insurance compa-nies, but without question his smartest acquisition was a person—Ajit Jain, whom he hired to run the Berkshire Hathaway Reinsurance

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Group. Ajit, born in 1951, earned an engineering degree at the pres-tigious Indian Institutes of Technology. He worked for IBM for three years, then enrolled at Harvard to gain a business degree.

Although Ajit had no insurance background, Buffett quickly recognized his brilliance. From a starting point in 1985, Ajit built the Reinsurance Group ’s fl oat (premiums earned but losses not paid) to $34 billion in a little over 20 years. According to Buffett, Ajit “insures risks that no one else has the desire or the capital to take on. His operation combines capacity, speed, decisiveness, and most importantly, brains in a manner that is unique in the insurance business.” 22 Not a day goes by without Buffett and Ajit having a con-versation. To give you an idea of Ajit ’s value, in the 2009 Berkshire annual report, Buffett wrote, “If Charlie, I and Ajit are ever in a sink-ing boat—and you can only save one of us—swim to Ajit.”

The Man and His Company

Warren Buffett is not easy to describe. Physically he is unremark-able, with looks that are more grandfatherly than corporate titan. Intellectually he is considered a genius, yet his down-to-earth relationship with people is truly uncomplicated. He is simple, straightforward, forthright, and honest. He displays an engaging combination of sophisticated dry wit and cornball humor. He has a profound reverence for those things logical and a foul distaste for imbecility. He embraces the simple and avoids the complicated.

Reading his annual reports, one is struck by how comfortable Buffett is quoting the Bible, John Maynard Keynes, or Mae West. Of course the operable word is reading . Each report is 60 to 70 pages of dense information: no pictures, no color graphics, no charts. Those disciplined enough to start on page 1 and to continue uninter-rupted are rewarded with a healthy dose of fi nancial acumen, folksy humor, and unabashed honesty. Buffett is very candid in his report-ing. He emphasizes both the pluses and the minuses of Berkshire ’s businesses. He believes that people who own stock in Berkshire Hathaway are owners of the company, and he tells them as much as he would like to be told if he were in their shoes.

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The company that Buffett directs is the embodiment of his personality, his business philosophy (which is identically tied to his investment philosophy), and his own unique style. Berkshire Hathaway, Inc. is complex but not complicated. There are just two major parts; the operating businesses and the stock portfolio, made possible by the earnings of the noninsurance businesses and the insurance companies ’ fl oat. Running through it all is Warren Buffett ’s down-to-earth way of looking at businesses he ’s consider-ing buying outright, a business he ’s evaluating for common stock purchase, or the management of his own company.

Today, Berkshire Hathaway is divided into three major groups: its Insurance Operations; its Regulated Capital-Intensive Businesses, which includes MidAmerican Energy and the rail-road Burlington Northern Santa Fe; and Manufacturing, Services and Retailing Operations, with products ranging from lollipops to jet airplanes. Collectively, these businesses generated, in 2012, $10.8 billion in earnings for Berkshire Hathaway compared to the $399 million Buffett the businessperson earned in 1988. At year-end 2012, Berkshire Hathaway ’s portfolio of investments had a market value of $87.6 billion against a cost basis of $49.8 billion. Twenty-fi ve years ago, in 1988, Buffett the investor had a portfolio valued at $3 billion against a cost basis of $1.3 billion.

Over the past 48 years, starting in 1965, the year Buffett took control of Berkshire Hathaway, the book value of the company has grown from $19 to $114,214 per share, a compounded annual gain of 19.7 percent; during that period, the Standard & Poor ’s (S&P) 500 index gained 9.4 percent, dividends included. That is a 10.3 percent relative outperformance earned for almost fi ve dec-ades. As I said earlier, when the “money changer” shut down the Buffett Partnership, he was just getting started.

Five-Sigma Event

For years academicians and investment professionals have debated the validity of what has come to be known as the effi cient market theory. This controversial theory suggests that analyzing stocks is a

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waste of time because all available information is already refl ected in current prices. Those who adhere to this theory claim, only partly in jest, that investment professionals could throw darts at a page of stock quotes and pick winners just as successfully as a sea-soned fi nancial analyst who spends hours poring over the latest annual report or quarterly statement.

Yet the success of some individuals who continually beat the indexes—most notably Warren Buffett—suggests that the effi cient market theory is fl awed. Effi cient market theoreticians counter that it is not the theory that is fl awed. Rather, they say, individuals like Buffett are a fi ve-sigma event, a statistical phenomenon so rare it practically never occurs. 23 It would be easy to side with those who claim Buffett is a statistical rarity. No one has ever come close to repeating his investment performance, whether it was the 13-year results from the Buffett Partnership or the almost fi ve-decade per-formance record at Berkshire Hathaway. When we tabulate the results of almost every investment professional, noting their inabil-ity to beat the major indexes over time, it prompts the question: Is the stock market indeed unassailable, or is it a question of the methods used by most investors?

Last, we have Buffett ’s own words to consider. “What we do is not beyond anyone else ’s competence. I feel the same way about managing that I do about investing: it is just not necessary to do extraordinary things to get extraordinary results.” 24 Most would dis-miss Buffett ’s explanation as nothing more than his special brand of Midwestern humility. But I have taken his word on the matter, and it is the subject of this book.

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Bonds Are Not ForeverThe Crisis Facing Fixed Income InvestorsSimon A. Lack978-1-118-65953-3 • Hardback • 240 pages • October 2013

Buy Now!


£26.99 £16.19 / €32.00 €19.20 / $40.00 $24.00


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1

C H A P T E R 1

FROM HIGH SCHOOL TO WALL STREET— THE BULL MARKET BEGINS

Inflation Memories

It was February 1972, and at nine years old I found playing with my toy soldiers in the flickering candlelight an exciting change from the steady illumination of incandescent bulbs. My British platoon skill-fully maneuvered behind the German lines, taking advantage of the shadows to surprise and quickly overwhelm the enemy. In those days the Germans were always the competition, whether on the battlefield or the English football pitch. The change in routine caused by the loss of electricity thrilled me as a young boy, but was not so excit-ing for my grandparents because it was a scheduled loss of power whose timing had been announced in the daily newspaper. February in Britain is dark at the best of times. After a long winter night, a per-son awakes to a dull, gray sky. By the time I began my career working in London ’s financial markets, the British winter, while not nearly as cold as that of New York, felt rather like two months living at the bottom of a damp, dark pit, with only an occasional glimpse of day-light through a window. However, an English evening in July, when the days are long but never humid, can be the best place in the world.

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2 BONDS ARE NOT FOREVER

Britain in the early 1970s was at the mercy of the trade unions, and a coal miners ’ strike was preventing fuel from reaching the power stations around the country. The proud people of a nation that still recalled the empire on which “the sun never set” found itself powerless at home, reduced to eighteenth-century means of illumination. Arguably, Britain was continuing its steady relative decline from the late nineteenth century, at which time the United States began to surpass Britain by measures such as iron and energy production, and industrial output (Kennedy, 1987). The steady rise in importance of other powers accelerated following World War II, when victory was achieved only at an enormous financial and material cost; confirmation of Britain ’s reduced status came during the 1956 Suez Crisis when U.S. pressure forced an embarrassing climb down on a once dominant power. Yet diminished global influ-ence didn ’t need to translate into self-destructive actions at home. Nonetheless, in 1972, while the trade unions and the government argued over pay, a country once described as “built on coal” was unable to use enough of it to light its homes. There were many low points for Britain and its economy in the 1970s when I was grow-ing up, including a bailout by the International Monetary Fund (IMF) in 1974.

Looking back at those times from a distance of 40 years and 3,500 miles in America, the 1970s were the most turbulent economic times since the Depression in the 1930s. Britain had its own set of home-made wounds in the form of militant trade unions, a manufacturing base that was losing out to its European competitors (especially the Germans), and a welfare state whose safety net was so generous it often made paid employment more costly than indolence.

Although Britain had its own partly self-inflicted problems, rising inflation in the 1970s and early 1980s wasn ’t limited to the United Kingdom. President Ford even resorted to handing out pins labeled Whip Inflation Now (WIN), perhaps revealing the paucity of more robust ideas within his administration. For much of the developed world it was the greatest inflation in living memory. Today, it is recounted through bland numbers on a statistical release from the U.K. government. In 1972, when the miners were forcing Britain to her knees, inflation the United Kingdom was 7.6 percent (see Figure 1.1 ).

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From High School to Wall Street—The Bull Market Begins 3

Two years later, fueled in part by generous pay settlements won by the coal miners and other unions, it was 19.2 percent. A year later, in1975, U.K. inflation reached 24.9 percent, a level at which money loses half its value in just over three years. In one month (May 1975), prices jumped 4.2 percent, an annualized inflation rate of 63.8 percent!

This is an abstract notion for most Westerners today. We read about inflation in Latin America, about hyperinflation in countries such as Zimbabwe, but few of us below the age of 60 have had to manage a household budget and make personal financial decisions under such circumstances. That includes me, but memories of my mother and grandparents worrying about “the cost of living,” about weekly price increases and the ongoing failure of income to keep up with expenses remain a part of my otherwise quite happy childhood.

Running commentary at the dinner table about how the price of sugar, washing powder, petrol, or school uniforms had gone up since the last time we gathered were a staple part of the conversation. Of course, nobody knew when it would end, or really even what was causing it (although the reasons seem clear enough to today ’s economic historians). People blamed the trade unions for selfishly

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008

FIGURE 1.1 U.K. Inflation 1948–2012

Source: U.K. Government, Office for National Statistics.

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negotiating pay increases not backed by improved productivity, the government for conceding to their demands, and the Organization of Petroleum Exporting Countries (OPEC) for sharply hiking the price of oil. All of these were to blame. What was worse was that at the time nobody knew if double-digit inflation or worse was a per-manent part of the economy.

AS BAD AS IT GETS

Hard economic times were not limited to Britain, though. The 1970s were tumultuous in America as well. While American trade unions were not nearly as powerful as their U.K. counterparts, photos of gas-guzzling cars lined up waiting to refill their tanks became an iconic image of that time. Shortages of basic goods, often accompanied by inflation, were a global phenomenon. The lax monetary policies followed by central banks and governments combined with some features unique to each country. In Britain, a steady loss of competi-tiveness, on top of an overly generous welfare state, was ultimately reversed by Maggie Thatcher when she came to power in 1979. In the United States, blame for the economic turbulence of the 1970s typically traces back to the 1960s, with the costs of financing the Vietnam War coincident with an expansion in welfare under Lyndon Johnson ’s “Great Society.” The subsequent loss of confidence in the U.S. dollar led to the breakdown of the Bretton Woods Accord when President Nixon suspended its free convertibility into gold in 1971. This ushered in the current era of “fiat money,” in which a currency ’s value is only as good as the market ’s confidence in its government ’s policies.

The 1970s and early 1980s saw two major oil price hikes, eco-nomic upheaval, and ultimately strong leaders in Margaret Thatcher and Ronald Reagan, determined to lead their respective coun-tries along a better path to smaller government, sound money, and improved living standards. Britain and America share a great deal in terms of history and values. At that time, both countries were in need of decisive leadership to promote economic growth supported by competitiveness and sound money. Both found it.

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In 1980, U.K. monthly inflation was 15 percent (in just one month, April 1980, prices rose 3.4 percent), and shortly thereafter the greatest bull market in history began in bonds. It followed the longest global bear market in history, one that began in 1946 after World War II and lasted 35 years. To illustrate, if a constant maturity 2.5 percent 30-year bond had been available throughout this period, its price would have declined from 101 to 17, a drop of 83 percent (Homer and Sylla, 2005). More than an entire generation of bond investors had lived through a relentless destruction of the purchas-ing power of their savings. In the years leading up to 1981 inves-tors had been demanding ever higher yields on their fixed income investments to provide protection against the rapid erosion of pur-chasing power. High borrowing costs were stifling any industry that required borrowed money to operate, which is to say virtually the entire economy. As financial markets began to sense that inflation and interest rates were peaking, they bid up the prices of bonds aggres-sively. The long road to low and stable inflation had begun, and with it a bull market in equities as well (propelled by falling borrowing costs, which were helping so many companies).

TRADING IN GILTS

By coincidence, my career in financial markets began in London within a few weeks of that peak in interest rates and inflation. I had grown up during the most extended financial turmoil in liv-ing memory, with double-digit interest rates and savings that rapidly lost their real (i.e., inflation-adjusted) value. I began my career in finance within a month or two of the very worst of high interest rates and rampant inflation. It was the threshold of the gradual return to sound money, and it would be complemented by an inexorable rise in the value of all financial assets. At the same time, finance and financial markets were set to gain enormously in importance through greater employment and would contribute a substantially larger share of overall economic output. Liberalization of markets would lead to a dizzying array of financial instruments to be traded. This occurrence combined with the relentless fall in trading costs would support the

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steady increase in financial engineering and debt creation that culmi-nated in the crash of 2008. None of this was even remotely plausible to someone recently out of high school and beginning his career in “The City.” Yet, in hindsight, my entry into the workplace was blessed with fortunate timing.

The U.K. market for government bonds, or “gilts” as they are known in Britain, has as long a history as any in the world. Consolidated annuities (known as “consols” for short) are perpetual securities that were created in 1756 by consolidating a series of already issued per-petual annuities. They have no maturity date (although theoretically the U.K. government may redeem them). Their history is detailed in a 2005 book soporifically named A History of Interest Rates by Sidney Homer and Richard Sylla. It ’s probably not flying off the shelves at Amazon. Nevertheless, for those interested in such things it is a com-prehensive record of the cost of borrowing that goes back to biblical times in measuring the price of credit.

Bond markets are not nearly as exciting as stocks. Bonds issued by governments don ’t involve colorful CEOs, corporate takeovers, or profits warnings. Bonds are boring; in fact, bonds are meant to be boring. Investors don ’t buy them for excitement—for thrills they buy stocks or go to the racetrack. Because bonds move far less than stocks and are rarely prone to the extremes of greed and fear so prevalent in equity markets, the people who traffic in them tend to be more staid as well.

Equity traders have been known to accuse their colleagues in bonds of being communists. On days when the government releases weak economic data, government bond prices often rise (because their yields fall), and traders in most markets generally do better when prices are rising. Economic misery, which tends to restrain inflation, causes bond traders to leap for joy while equity markets and consumer sentiment both tumble. There ’s an essential difference in outlook between the two markets. Equity traders are happiest when they are optimistic on the economic outlook because higher corpo-rate profits tend to fuel rising stock prices. By contrast, bond traders are often cheerful when everybody is miserable. Rising unemploy-ment, slowing retail sales, and falling house prices are all associated with falling interest rates and a bull market for bonds. Try watching

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the professionals on TV from any big bond firm (Pimco, for example) sincerely lament another weak economic report while their invest-ments are most likely rising in price. Professed and genuine concern for the newly unemployed competes with the quiet satisfaction of a more highly valued bond portfolio.

The U.K. gilt market (so named after the “gilt-edged” credit qual-ity of the bonds traded there) of 1980 operated in a way that was scarcely different from the 1880s. The market consisted of brokers, who charged a commission and traded with the public as brokers do, and jobbers who were market makers and did not deal with the pub-lic at all. The market was structured with two large jobbers named Wedd Durlacher and Akroyd and Smithers, in effect surrounded by a far larger number of brokers. Brokers were allowed to trade only with jobbers and investors, not with one another. The jobbers could not trade with anybody except the brokers or (occasionally) with other jobbers. The jobbers held a monopoly on market making, but in return had given up the ability to face investors. The brokers had the exclusive right to deal with the general public, and in exchange were allowed to act only as agents (i.e., they couldn ’t take positions themselves).

Business took place on the large floor of the London Stock Exchange. Jobbers stood at their “pitch,” or assigned post, while bro-kers moved around the floor in search of the best deal for their client. A broker would ask a jobber to quote a price that was, in the best tradition of London markets, always “two-way” (i.e., bid and offer). Years later, when I was trading U.S. government bonds in New York, I always felt that the U.S. custom, whereby the client had to dis-close whether they were buying or selling before obtaining a quote from the dealer, was providing a needless advantage at the expense of the client. A U.S. government bond dealer will show only one side of a two-way market—the client will ask for “a bid on 25,” for example, or request that the trader “offer 50.” Showing a two-way market keeps the dealer honest, in that if his bid/ask spread is wide, that ’s an indication that his profit margin is possibly too high and may signal the client to go elsewhere. Other markets, such as foreign exchange, always required that the market maker quote a two-way price. The trader could try to guess whether the client was buying

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or selling, but if he shaded the price the wrong way, he ran the risk of the client ’s trading on the other side (i.e., buying when the dealer thought he was a seller) and perhaps profiting off the dealer ’s attempt to “read” him.

The London Stock Exchange in 1980 was only a few years away from “Big Bang,” the 1986 deregulation of the overall market that would radically alter almost everything about how “The City,” as London ’s financial center is called, operated. Back then, the entire place followed rigid work practices, from commissions, which were uniform across all firms, to career paths and how clients transacted their business. Finance had long provided jobs for those who were quick-witted and confident. London ’s financial market place is physically not far from the East End of London, with its rowhouses of tenements barely changed from World War II. Multiple paths existed for the aspiring financier: education at a private school (perversely called a “public” school in the United Kingdom) followed by a university degree, then entry to a blue-blooded stockbroker in the gilt market. This was dubbed by some the “champagne and polo crowd,” evoking the cultural background of those whose leisure regularly includes the enjoyment of both.

THE OLD CLASS STRUCTURE

Another path was from comprehensive (i.e., not elite) school, and probably not university, to a job in the equity markets or the money markets, where one ’s peers would be the “gin and tonic and squash crowd,” denoting less cultured and cheaper relaxation. The open out-cry, rough and tumble of a large physical market was a comfortable place for someone who might just as easily be competing to sell fruit and vegetables fewer than 10 miles away for vastly different com-pensation. London has become a much more culturally diverse place, with little patience for the staid old ways, and that ’s no doubt a good thing. Still, the London Stock Exchange in 1980 in many ways mir-rored the class system of the country. Britons could instantly place someone in their appropriate class as soon as words were spoken, and, while business could be transacted across class lines, social life was rarely so flexible.

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Forest School in Snaresbrook is close to London ’s East End. The surrounding forests from which it draws its name quickly give way to gritty working-class neighborhoods as you head toward the cen-ter of the city. Before reaching the gleaming towers of London ’s financial district, it ’s necessary to pass through run-down areas such as Leyton, Hackney, and Bethnal Green, none of which could be confused with the leafy suburbs of the stockbroker belt. Historically, immigrants to the United Kingdom have often settled in the East End, from the Huguenots fleeing religious persecution in France in the seventeenth century to the South Asians today. Forest was and remains a public school with neighbors who can only dream of affording the tuition to send their children there, and yet the presence of so many minority students highlights the economic mobility that immigrants achieve. In many ways, my alma mater, Forest School, was typical—all boys, classes that ran six days a week, with a heavy emphasis on competition across all endeavors, both academic and sporting. When I was there in the 1970s, there were many boys that didn ’t look “English,” to use the terminology of that time, because they weren ’t white. Today ’s coeducational student body is no less diverse, and yet more “English” because the country is itself more diverse.

The closely packed houses of London ’s East End have usually been home to workers struggling to move up a rung or two, and also home to a fair amount of crime. A student from Forest School, easily recog-nizable in his uniform, would head warily in that direction to a place where looking at someone the wrong way, or indeed looking at them at all, was to invite trouble. So this public school ’s catchment area for students included parts of London that wouldn ’t normally send their children to one. Nonetheless, the experience was typical of most public schools. Boys were assigned to “houses,” which were the basis for intense internal competition in everything from sports to drama. In fact, competition was ever present, whether it was in class rankings for subjects or an English football game with a neighboring school. Anything that mattered was subject to comparison with your peers.

“Monitors” (selected students in their senior year) were the first layer of sometimes arbitrary discipline, empowered to admin-ister corporal punishment if they judged it appropriate. It was its

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own somewhat insular and challenging world, with far less parental involvement than is the case in most schools today. School was a tight community, where problems were invariably resolved with little out-side influence. You had to figure things out within the confines of the physical boundaries and the social ones. Therefore, I found the seven years I spent there hugely impactful, as those years often are.

The school ’s song, in Latin, was sung on key days during the year, and portraits of headmasters past adorned the walls of the dining hall where grace was said (in Latin) before boys could eat their (usually barely edible) lunch. The hierarchy and the traditions were all part of the education, in addition to the academic experience. Although fewer than 10 percent of the population shared this type of school-ing, they represented a far bigger percentage of the U.K. workforce in law, medicine, senior levels of the government, and, of course, finance.

On top of this unusual mixing of social classes, I took the less conventional route out of school and went straight to work in The City, passing up university out of the poorly informed, youthful con-fidence that my formal education was already sufficient. I soon found myself with the champagne and polo crowd in U.K. government bonds, known as the gilt market, in spite of the absence of a univer-sity degree on my resume. I was a “blue button,” so named after the blue badge with my employer ’s name on it that placed me precisely at the bottom of the ladder. In many ways, the gilt market was like starting school again, with my firm taking the place of my school-house and my blue button status ensuring that the yellow badges (members) and silver badges (partners) barely even acknowledged my existence, just as senior-year students in school barely tolerate the existence of those merely a few years younger.

Gilts were the preserve of the “well-spoken” public schoolboys who had grown up in elite establishments steeped in practices many decades old. In a memorable holdover from much earlier times, the employees of one stockbroking firm called Mullins were all required to wear top hat and tails every day on the trading floor. Socially, they were the top of the pyramid, drawing their employees from only the most exclusive public schools. They were truly in the champagne and polo crowd.

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A NINETEENTH-CENTURY MARKET

Mullins retained a special designation in that they were the only firm allowed to trade directly with the U.K. Treasury. In an archaic struc-ture that epitomized the Old World style of business and fed many along the food chain, the U.K. government would issue its new gilts only to Mullins. Mullins would then turn around and sell these on to the jobbers, who would buy only what they knew they could sell back to the other stockbrokers, who would then sell them at very high commissions to the investing public. It was emblematic of the closed, anticompetitive methods of the time.

The brokers from Mullins followed a long tradition of dressing somewhat like the students from Eton, perhaps Britain ’s most elite public school and from which, no doubt, many of them had grad-uated. Their nineteenth-century dress code persisted until the late twentieth century. When the Big Bang in 1986 transformed com-missions, structure, and customs, this particular tradition went, too, as Mullins was absorbed by investment bank S. G. Warburg and the gilt market abandoned the physical trading floor in favor of doing busi-ness over the phone. I don ’t think it ’s missed, although it ’s extraordi-nary to think that even within my 30+ year career they were part of the landscape.

In addition, just as moving from first year to sixth year in school can ’t realistically be completed in fewer than five years, graduating to the next level as a stockbroker in the gilt market required as much as anything that you “do your time.” The rigidity of commissions and market practices required a similarly inflexible career path, in which talent or ambition would take second place to chronologi-cally determined promotions. For me, my impatience with this way of business culminated with a discussion of my performance and my first pay raise. I entered the boardroom to meet with my boss, having put on my suit jacket, as was the custom for such a formal discus-sion. My diminutive annual salary of £2,750 was surely about to be rounded up to £3,000. To my dismay a mere £200 was added, confirming my lowly position at the base of the ladder in contrast to my own inestimable self-worth. Shortly afterward, I concluded that the gilt market ’s time frame and mine were at odds, and I moved to

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the money markets, where my starting salary as a trainee broker was quickly agreed at £5,000.

So I left the rigid social confines of the London Stock Exchange, where your accent would assign you to the equity market (working class, gin and tonic and squash) or the gilt market (upper class, cham-pagne and polo, although in my time there I experienced neither). Instead, I entered the money markets, where social classes mingled, the business environment was more freewheeling, and ability might just get you a step ahead.

FINANCE STARTS TO GROW

I was one individual making personal decisions that were dictated by the world I found but to whose shifting circumstances I did not give much thought. The United States and Britain were at the threshold of an advance in financial services that would substantially increase their impact on future economic growth. A 2012 paper by Robin Greenwood and David Scharfstein, both of Harvard Business School and the National Bureau of Economic Research (NBER), examines this shift in some detail (Greenwood and Scharfstein, 2012). The authors focus on a concept called gross domestic product (GDP) value added. Rather than measure the simple output (i.e., revenue) of an industry, they believe the more important measure is the value added. This makes sense since any business has inputs that it needs to generate its output. To use an example, a supermarket might take in $100,000 of revenue in a week and only spend $80,000 buying all the produce from various wholesalers. The $20,000 remaining goes to pay compensation to the workers in the supermarket and profit to the owners. It ’s this $20,000 that is the GDP value added measure used by the authors, essentially salaries and bonuses to the workers in financial services and profits to the owners of the businesses. As such, it excludes all the other inputs or expenses, such as leased office space, information technology (IT), and others. These are someone else ’s GDP value added. They are not directly created by the bankers, brokers, and asset managers in finance.

Greenwood and Scharfstein found that financial services ’ share of U.S. GDP measured in this way grew from 4.9 percent in 1980 to

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8.3 percent 1 in 2006, where it peaked just prior to the mortgage crisis that began in 2007 (see Figure 1.2 ). In 1950, finance was only 2.8 percent of GDP, so although it had been growing as a proportion of GDP prior to 1980, the annual rate of growth doubled pre-1980 versus post-1980 (from 0.07 percent per annum to 0.13 percent per annum). Britain experienced a similar though less marked increase because its economy was already more biased toward finance than the United States at that time. Canada, Japan, and the Netherlands all saw an increase in finance within their economies, although it was by no means a worldwide phenomenon. In many European countries the opposite effect was observed, as other industries gained a big-ger share of overall economic output. Germany, France, and Italy all saw modest falls in financial services ’ share of GDP over this period, while in Norway and Sweden the share dropped by over a third.

The authors don ’t dwell much on the reasons behind these dif-ferent outcomes. In looking at the data, it ’s clear that those countries

1 Current Bureau of Economic Analysis data show finance at 8.2 percent in 2006, pre-sumably the result of a revision in the data since the Greenwood and Scharfstein paper was published.

4%

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

5%

6%

7%

8%

9%

FIGURE 1.2 U.S. Financial Services Percentage of GDP

Source: Bureau of Economic Analysis.

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with a longer history and more dominant role in financial markets were the ones that witnessed the growth. During this time, there was a growing focus on the need to be global and to have scale in order to thrive. I worked during most of this period at one large American bank, which morphed from Manufacturers Hanover Trust to Chemical Bank to Chase Manhattan, before winding up as the behemoth that is JPMorgan today. Many smaller acquisitions took place along the way, and the constant strategic justification was the need to provide a global platform to our global clients.

Furthermore, banking is also heavily reliant on IT and the devel-opment of the Internet from the mid-1990s improved communica-tions dramatically, allowing more trading functions to be managed in a smaller number of major financial centers. Language and common culture no doubt also played a role, and with spoken English as well as U.K. law already the common currency across many areas of bank-ing, the British Empire and its former members had a big lead. The fact that the United States was the largest economy, market, and only superpower is probably a factor, too.

London already had a dominant position in this sector through-out Europe. These trends probably served to marginalize centers like Brussels, Paris, and Milan. New York never really had a close com-petitor within its time zone, although Chicago ’s futures pits made it the home for exchange traded derivatives. It ’s therefore likely that for these reasons and maybe others, the Anglo-Saxon countries allowed and encouraged bankers and asset managers to play a bigger role in their economies. It ’s doubtful that the political leaders of the late 1970s and early 1980s sought this transformation, and the past 30 years have witnessed an evolution with many twists along the way, as the creative destruction that defines capitalism has created winners and losers. The way the French sneer at Anglo-Saxon hedge funds and their brand of capitalism may reflect different values that led France to inhibit similar growth in their domestic markets. Perhaps it also reflects disappointment that so many young French people choose to live and work in London, where the opportunities are often far greater.

The GDP data from which this analysis is drawn identifies two areas within financial services that are responsible for most of the

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growth—securities and credit intermediation. Insurance is the third big component of financial services, although its growth over this time was unremarkable and fairly steady going back as far as 1940.

The securities industry, which includes everything from trading and underwriting to asset management, increased its share of GDP value added from 0.4 percent in 1980 to 1.9 percent in 2006 before falling back modestly to 1.7 percent in 2007 (see Figure 1.3 ). This more than quadrupling of virtually all things related to investment securities in barely more than a single generation is probably unprec-edented in history. The securities industry further breaks down into subcategories, of which asset management is by far the biggest, repre-senting over half of all securities industry activity by 2007.

Credit intermediation, which includes traditional banking such as taking deposits and making loans, also saw substantial growth albeit from a higher base. This increased from 2.6 percent of GDP value added in 1980 to 3.6 percent in 2006 before dropping back in 2007 to 3.4 percent, although by 2011 it had increased modestly back to 3.6 percent (Bureau of Economic Analysis, 2013). Banking went

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from being six times as big as the securities industry in 1980 to only twice as big almost 30 years later, although it, too, represented a big-ger share of the economy.

IS FINANCE GOOD?

So Wall Street and Banking (and sometimes the two are synony-mous) had by 2006 reached over 8 percent of the entire U.S. econ-omy. As we all discovered during the 2007-2008 Crisis, their actual impact was substantially greater than this, since their collapse led to the worst recession most of us have ever seen and the brink of finan-cial catastrophe. These two industries affect the lives of so many more people than simply those employed within it. As well as employing more workers, finance has contributed to the increasing dispersion of incomes within most developed countries. Many finance jobs provide more than your average middle-class income that has stag-nated for the past 10 years. Indeed, from 1980 to 2006, pay in finance rose cumulatively 70 percent more than in the rest of the economy (Philippon, 2008).

The growth in the securities industry and in credit intermediation were related phenomena. Much of the growth in credit interme-diation was fueled by residential mortgages. The long bull market in bonds created regular incentives for homeowners to refinance their mortgages to take advantage of lower rates. At the same time, public policy became geared toward increased home ownership, while the tax deductibility of interest on home mortgages combined with the increased percentage of loans underwritten by the federal govern-ment, all contributed to the increased percentage of families living in their own homes.

Data from the U.S. Census Bureau shows that the home owner-ship percentage was remarkably stable from 1965 until the late 1990s, fluctuating between 63 percent and 66 percent. President Clinton made increasing home ownership one of his goals, stating to the National Association of Realtors in November 1994 with his typical eloquence that “most Americans should own their homes, for reasons that are economic and tangible, and reasons that are emotional and

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intangible, but go to the heart of what it means to harbor, to nour-ish, to expand the American Dream” (Morgensen, 2011). Clinton enlisted support from all the stakeholders including banks, securities firms, builders, and realtors, and his strategy was greatly facilitated by the corruptly led twin federal agencies FNMA and FHMC (Fannie Mae and Freddie Mac) (Morgensen, 2011).

By the late 1990s the home ownership percentage had reached the top of its multidecade band of 66 percent (see Figure 1.4 ). By 2000 it was at 67 percent and in 2004 it reached 69 percent before moderating for a few years and then falling more sharply back to its long-term range as the housing bubble burst. Government pol-icies were aided by increased securitization of mortgages, and the increased securitization also led to a bigger securities market with more assets to manage for the securities industry. In this way, the two fastest-growing areas in financial services were linked and to some degree fed off one another.

Some compelling questions are prompted by the developments of the past 30 years. Society may well challenge the wisdom of promot-ing home ownership beyond what was, in hindsight, a stable, equilib-rium level. Owner-occupied homes are widely believed to promote

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FIGURE 1.4 U.S. Home Ownership Percentages

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stable communities with lower crime rates and higher incomes; how-ever, the incentives to own your own home clearly resulted in many people buying homes they could not afford, with mortgages they should not have been given. While the policies that promoted this were no doubt well intentioned, the sad outcome of so many people losing their homes, and in many cases a hard-earned down payment, exposed the flawed nature of this approach.

Household debt also grew along with Wall Street. Outstanding consumer credit jumped in the 1950s, as the end of World War II brought soldiers home and ushered in the beginning of the Baby Boom and increased household formation. It then fluctuated between 10 and 13 percent of GDP during the 1960s and 1970s (see Figure 1.5 ). Nevertheless, from 1980 to 2003, consumer credit grew steadily from 12.6 percent of GDP to 18.6 percent. Although during recessions it shrank, the overall trend was clearly higher. There ’s little doubt that securitization aided the process as banks packaged debt into bonds and moved it off their balance sheets to investors globally.

Government debt (federal, state, and local) also grew strongly from 1980. No doubt, the growth of finance helped this as well. As a percentage of GDP, government debt is close to the levels following

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World War II (see Figure 1.6 ). When combined with household debt, our total obligations are assuredly at a record.

Another important question is whether the growth in financial services has created widespread benefits for anybody beyond those directly employed in the industry. Greenwood and Scharfstein con-clude that a bigger asset management industry has led to higher equity prices than would otherwise be the case through greater investor diversification. Their logic is that investors hold generally more diversified portfolios of equities, thanks to the greater use of financial advisers and mutual funds. In theory, this improved diversifi-cation should lower the return required for investors to hold equities (because portfolios are now less risky through being more diversi-fied). A lower required return for equity investors translates directly into a lower cost of equity capital for public companies.

It ’s a reasonable argument, albeit hard to prove empirically. Cheaper access to equity financing is most certainly good for the broader economy, since it makes it easier for companies to finance themselves and invest in new projects, with corresponding broad-based benefits throughout the economy. Yet they also note that asset management fees have stayed surprisingly high and that there seem to be few economies of scale that pass through to the investor in

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terms of lower fees. In some respects, they echo the findings in my 2011 book, The Hedge Fund Mirage: The Illusion of Big Money and Why It’s Too Good to Be True , in which I showed that hedge fund manag-ers had kept all the profits made with their clients ’ capital through exorbitant fees. This is an extreme case of the financial services indus-try retaining substantially all of the benefits of a potentially good thing (active asset management). It nonetheless begs the question of whether such behavior is simply rent seeking with little added societal value. Increasing dispersion of incomes and the stagnation of median household real wealth suggest that gains have been unevenly distributed. Politically, the median voter ’s economic state is far more important than the average voter ’s when the two are diverging, as is the case today. As average incomes are less reflective of the average person (due to “the 1 percent” doing so well and pulling up the aver-age), a public policy response cannot be far behind.

INVESTING AFTER THE BUBBLE

Perhaps the most interesting question is the one facing investors. We are probably at an inflection point in two important ways. The col-lapse in the real estate bubble with its consequently deeply unpopu-lar bank bailouts has focused attention on the securities industry, its pay practices, and what the appropriate relationship should be between banks and the society they are intended to serve. At its core, Wall Street is supposed to facilitate the channeling of savings into productive types of capital formation, which will foster economic growth and job creation as well as investor returns above inflation. To many people, Wall Street has increasingly lost sight of this goal; one simple example is the growth of computerized, high-frequency trading (HFT). Managers of HFT strategies even value physical proximity to the New York Stock Exchange so as to gain vital mil-liseconds in the transmission of their orders and therefore a more profitable outcome. It ’s hard to come up with a more obvious case of a perfectly useless activity that is clearly part of a zero-sum game on whose other side lie conventional investors seeking a return on their capital.

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Public policy is just beginning to grapple with all the issues of a financial system that may be larger than we need, a system that although highly competitive within itself doesn ’t appear to pass on the benefits of that competition to consumers in the form of lower prices. Increased regulation and higher capital requirements are the two most obvious reactions, although in time society may add further constraints.

The other inflection point is surely on the level of debt outstand-ing. For if there ’s one common thread linking up the U.S. real estate crash, the subsequent Euro sovereign debt crisis, and the looming U.S. fiscal crisis over entitlements and taxes, it must be an excess of debt across individuals and their governments. Public corporations with no taxing ability or social safety net have broadly been the sec-tor that has been best behaved, which is why cash held by corpora-tions is at a record high.

The enormous debts incurred by individuals and their govern-ments, including future commitments of pensions and health care that don ’t show up on conventional public reporting, represent per-haps the most important consideration for investors today. Whether the huge liabilities we have created result in a lost decade like Japan ’s through deflation or are highly inflationary is, to me at least, not clear. Yet, we are likely entering a period of greater populism fueled by increased income disparity, and perhaps more popular support for debtors who are both more numerous and face darkening prospects through continually stagnant middle-class wages.

This book tells the story of how we arrived here, which is to say at a place with far too much debt owed by governments and individuals and with no easy ways to deal with it. The debt is not going away, and barring some unimaginable technological leap, our economies are unlikely to grow their way out of trouble. The story has two parallel strands: one describes the economic forces and trends that have been operating, in some cases the direct result of public policy decisions, while in others in spite of them. The other strand provides a ground-level view from one participant who, for most of this time, had little understanding of the larger forces at work, but was rather reacting to market forces in a micro way, choosing jobs and opportunities whose prospects seemed most promising. Only with the benefit of hindsight

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can I regard my own past in conjunction with the broad strokes of history and appreciate that I was responding to market forces as I saw them in terms of career moves I made and jobs I held. I gave little thought at the time to the invisible hand at work in the background. This was a period of increasing financial liberalization as markets deregulated, of increased borrowing greatly aided by securitization and a heavy public policy bias toward debt and real estate, and con-sequently the ability to consume today at the expense of tomorrow became easier for individuals as well as governments.

It would be natural to hold strong views and to express them in reviewing how we arrived here. However, there are many var-ied solutions, and the politics are largely for others to pursue. As an investor, you take the world as you find it, not as it should be; and while understanding the past is important in terms of planning for the future, investors need to focus themselves on likely outcomes and their probabilities and consequences, and make decisions accordingly. Most of us could solve the developed world ’s debt problems easily enough, given the absolute power to do so. Futile debates on how the world should be are far less interesting than coolly assessing how it may well turn out to be.

This story uses economic statistics to present the big picture com-bined with one individual ’s personal journey through the growth of financial deregulation, securities trading, and debt. By considering how we made the journey, the story seeks to answer the question most investors have—where should I invest for tomorrow? It will be no surprise given the book ’s title that the forces of economic history and politics are likely to combine in ensuring that even though fixed income has been a great place for investors over the past 30 years, the next decade is likely to be disappointing and may even be ruinous for bond investors. Those avoiding the possible risk of falling equity markets by holding bonds are most likely accepting the guarantee of negative real returns (i.e., returns below inflation, resulting in a loss of purchasing power) on their savings and a transfer of real wealth to those who have borrowed too much. Bonds have been great, to be sure, but Bonds Are Not Forever.

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The Dao of CapitalAustrian Investing in a Distorted WorldMark Spitznagel978-1-118-34703-4 • Hardback • 368 pages • October 2013

Buy Now!


£19.99 £11.99 / €24.00 €14.40 / $29.95 $17.97


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1

Chapter One

The Daoist Sage Klipp ’s Paradox

You ’ve got to love to lose money, hate to make money, love to lose money, hate to make money. . . . But we are human beings, we love to make money, hate to lose money. So we

must overcome that humanness about us.” This is “Klipp ’s Paradox”—repeated countless times by a sage old

Chicago grain trader named Everett Klipp, and through which I first happened upon an archetypal investment approach, one that I would quickly make my own. This is the roundabout approach (what we will later call shi and Umweg , and ultimately Austrian Investing ), indeed cen-tral to the very message of this book: Rather than pursue the direct route of immediate gain, we will seek the difficult and roundabout route of immediate loss, an intermediate step which begets an advantage for greater potential gain.

This is the age-old strategy of the military general and of the entre-preneur—of the destroyer and of the very creator of civilizations. It is, in fact, the logic of organic efficacious growth in our world. But when it is hastened or forced, it is ruined.

Because of its difficulty it will remain the circuitous road least trav-eled, so contrary to our wiring, to our perception of time (and vir-tually impossible on Wall Street). And this is why it is ultimately so

“

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2 T H E D A O O F C A P I T A L

effective. Yet, it is well within the capability of investors who are willing to change their thinking, to overcome that humanness about them, and follow The Dao of Capital .

How do we resolve this paradox? How is it that the detour could be somehow more effective than the direct route, that going right could be somehow the most effective way to go left? Is this merely meant to confuse; empty words meant to sound wise? Or does it con-ceal some universal truth?

The answers demand a deep reconsideration of time and how we perceive it. We must change dimensions, from the immediate to the inter-mediate , from the atemporal to the intertemporal . It requires a resolute, forward-looking orientation away from what is happening now, what can be seen, to what is to come, what cannot yet be seen. I will call this new perspective our depth of field (using the optics term in the temporal rather than the spatial), our ability to sharply perceive a long span of forward moments.

This is not about a shift in thinking from the short term to the long term, as some might suppose. Long term is something of a cliché, and often even internally inconsistent: Acting for the long term gener-ally entails an immediate commitment, based on an immediate view of the available opportunity set, and waiting an extended period of time for the result—often without due consideration to or differentia-tion between intertemporal opportunities that may emerge during that extended period of time. (Moreover, saying that one is acting long term is very often a rationalization used to justify something that is currently not working out as planned.) Long term is telescopic, short term is myopic; depth of field retains focus between the two. So let ’s not think long term or short term. As Klipp ’s Paradox requires, let ’s think of time entirely differently, as intertemporal , comprised of a series of coordinated “now” moments, each providing for the next, one after the other, like a great piece of music, or beads on a string.

We can further peel away Klipp ’s Paradox to reveal a deeper para-dox, at the very core of much of humanity ’s most seminal thought. Although Klipp did not know it, his paradox reached back in time more than two and a half millennia to a far distant age and culture, as the essential theme of the Laozi (known later as the Daodejing , but I will refer to it by its original title, after its purported author), an

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The Daoist Sage 3

ancient political and military treatise, and the original text and summa of the Chinese philosophy of Daoism.

To the Laozi , the best path to anything lay through its opposite: One gains by losing and loses by gaining; victory comes not from waging the one decisive battle, but from the roundabout approach of waiting and preparing now in order to gain a greater advantage later. The Laozi pro-fesses a fundamental and universal process of succession and alternation between poles, between imbalance and balance; within every condition lies its opposite. “This is what is called the subtle within what is evident. The soft and weak vanquish the hard and strong.” 1

To both Klipp and the Laozi , time is not exogenous, but is an endogenous, primary factor of things—and patience the most precious treasure. Indeed, Klipp was the Daoist sage, with a simple archetypal message that encapsulated how he survived and thrived for more than five decades in the perilous futures markets of the Chicago Board of Trade.

THE OLD MASTER

Daoism emerged in ancient China during a time of heavy conflict and upheaval, nearly two centuries of warfare, from 403 to 221 BCE, known as the Warring States Period, when the central Chinese plains became killing fields awash in blood and tears. This was also a time of advance-ment in military techniques, strategy, and technology, such as efficient troop formations and the introduction of the cavalry and the standard-issue crossbow. With these new tools, armies breached walled cities and stormed over borders. War and death became a way of life; entire cities were often wiped out even after surrender, 2 and mothers who gave birth to sons never expected them to reach adulthood. 3

The Warring States Period was also a formative phase in ancient Chinese civilization, when philosophical diversity flourished, what the Daoist scholar Zhuangzi termed “the doctrines of the hundred schools”; from this fertile age sprung illustrious Daoist texts such as the Laozi and the Sunzi , the former the most recognized from ancient China and one of the best known throughout the world today. Its attributed author, translated as “Master Lao” or “The Old Master,” may or may not have

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even existed, and may have been one person or even a succession of contributors over time.

According to tradition, Laozi was the keeper of archival records for the ruling dynasty in the sixth century BCE, although some scholars and sinologists maintain that the Old Master emanated from the fourth century BCE. We know from legend that he was considered to have been a senior contemporary of Kongzi (Confucius), who lived from 551 to 479 BCE, and who was said to have consulted Laozi and (despite being ridiculed by Laozi as arrogant) praised him as “a dragon riding on the winds and clouds.” 4 Furthermore, written forms of the Laozi , which scribes put down on bamboo scrolls (mostly for military strate-gists who advised feuding warlords), are likely to have been derivatives of an earlier oral tradition (as most of it is rhymed). Whether truth or legend, flesh and bones or quintessential myth, one person or many over time, the Old Master relinquished an enduring, timeless, and universal wisdom.

To most people, it seems, the Laozi is an overwhelmingly religious and even mystical text, and this interpretive bias has perhaps done it a disservice; in fact, the term “Laoism” has been used historically to distinguish the philosophical Laozi from the later religious Daoism. Recently, new and important translations have emerged, following the unearthing of archeological finds at Mawangdui in 1973 and Guodian in 1993 (which amounted to strips of silk and fragments of bamboo scrolls), providing evidence of its origins as a philosophical text 5 —not mystical, but imminently practical. And this practicality relates par-ticularly to strategies of conflict (specifically political and military, the themes of its day), a way of gaining advantage without coercion or the always decisive head-on clash of opposing forces. The Dao of Capital stays true to these roots.

The Laozi , composed of only 5,000 Chinese characters and 81 chapters as short as verses, outlines the Dao —the way, path, method or “mode of doing a thing,” 6 or process toward harmony with the nature of things, with awareness of every step along the way. Sinologists Roger Ames and David Hall describe the Dao as “way-making,” “ processional” (what they call the “gerundive”), an intertemporal “focal awareness and field awareness”—a depth of field—by which we exploit the potential that lies within configurations, circumstances, and systems. 7

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The Daoist Sage 5

The central concept permeating the Laozi is referred therein as wuwei , which translates literally as “not doing,” but means so much more; rather than passivity, a common misperception, wuwei means noncoercive action—and here we see the overwhelming laissez-faire , libertarian, even anarchistic origins in the Laozi , thought by some to be the very first in world history 8 (as in “One should govern a country as one would fry a small fish; leave them alone and do not meddle with their affairs” 9 —a cardinal Laozi political credo most notably invoked in a State of the Union address by President Ronald Reagan). The Laozi also has been deemed a distinctive form of teleology, one that empha-sizes the individual ’s self-development free from the intervention of any external force. This leads to the paradox of what has come to be known as wei wuwei (literally “doing/not doing,” or better yet “doing by not doing,” or “do without ado” 10 ). “One loses and again loses / To the point that one does everything noncoercively ( wuwei ). / One does things noncoercively / And yet nothing goes undone.” 11

In wuwei is the importance of waiting on an objective process, of suffering through loss for intertemporal opportunities. From the Laozi , “Who can wait quietly while the mud settles? Who can remain still until the moment of action?” 12 It appears as a lesson in humility and toler-ance, but, as we wait, we willingly sacrifice the first step for a greater later step. In its highest form, the whole point of waiting is to gain an advantage. Therefore, the apparent humility implied in the process is really a false humility that cloaks the art of manipulation; as French sinol-ogist François Jullien noted, “the sage merges with the manipulator,” who, in Daoist terms, “humbles himself to be in a better position to rise; if he withdraws, he does so to be all the more certainly pulled forward; if he ostensibly drains away his ‘self,’ he does so to impose that ‘self ’ all the more imperiously in the future.” 13 This is the efficacy of circum-vention camouflaged as suppleness. And in this temporal configuration is, in the words of Ames and Hall, the Laozi ’s “correlative relationship among antinomies”: 14 With false humility we deliberately become soft and weak now in order to be hard and strong later—the very reason that, in the Laozi , “Those who are good at vanquishing their enemies do not join issue.” 15

In this sense, the Laozi can simply be seen as a manual on gaining advantage through indirection, or turning the force of an opponent against him, through “excess leading to its opposite.” 16

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THE SOFT AND WEAK VANQUISH THE HARD AND STRONG

Perhaps the most tangible representation of wuwei can be seen in the interplay of softness and hardness in the Chinese martial art taijiquan —not surprising as it is a direct derivative of the Laozi . According to legend, taijiquan was created by a thirteenth-century Daoist priest, Zhangsanfeng. Cloistered on Wudang Mountain, he observed a clash between a magpie and a serpent, and suddenly fully grasped the Daoist truth of softness overcoming hardness. 17 The serpent moved with—indeed, complemented—the magpie, and thus avoided its repeated decisive attacks, allowing the snake to wait for and finally exploit an opening, an imbalance, with a lethal bite to the bird. In this sequential patience, retreating in order to eventually strike, was the Laozi ’s pro-found and unconventional military art:

There is a saying among soldiers: I dare not make the first move but would rather play the guest; I dare not advance an inch but would rather withdraw a foot.

This is called marching without appearing to move, Rolling up your sleeves without showing your arm, Capturing the enemy without attacking, Being armed without weapons. 18

Like Daoism itself, taijiquan has drifted into the more mystical and new age, but its roots remain in its martial application; this is clear today in the powerful blows of the original Chen style taijiquan form, as still practiced in Chen Village (located in Henan province in central China). According to Chen Xin (among the lineage of the eponymous Chen clan) in his seminal Canon of Chen Family Taijiquan , a deceptive rotational and circular force—known as “silk reeling”—is “the main objective of Taijiquan moves, which work on the centrifugal principles of a ‘roundabout’.” 19 The rotation is between retreating and advanc-ing, between soft and hard. (When performed by a master, such as my teachers Qichen Guo and Jwing-Ming Yang, of whose qinna maneuvers I have oft found myself on the wrong end, it is most unsettling, almost deplorable in its artful deceitfulness.)

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The Daoist Sage 7

Taijiquan is a physical manifestation of the importance of waiting and exploiting another ’s urgency through softness in a clash. This is most apparent in the two-person taijiquan competitive exercise known as tuishou , or “push hands,” in which two opponents engage in what looks to the casual observer like a choreographed series of synchro-nized movements. In actuality tuishou is a cunning contest with highly constrained rules, in which each tries to throw the other to the ground (or outside a boundary) during a sequence of subtle alternating feints and attacks. The real force is not in the pushing, but in the yielding. (In tuishou is an ideal roundabout and investing metaphor, one that I will return to again and again.)

The “Song of Push Hands,” in its oral transfer of the art over centu-ries in Chen Village, instructs the competitor to “guide [the opponent ’s] power into emptiness, then immediately attack.” 20 To guide or lure the opponent into emptiness and thus destroy his balance is the very

Tuishou: Zouhua and Niansui

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indirect objective—to gain the position of advantage—to be followed by the direct objective of attack. This is the essential tuishou sequence of yielding, neutralizing, and sticking. Yielding and neutralizing— zou or zouhua , “leading by walking away”—is the sneaky retreating rout, followed by converting and redirecting a force to advantage; that advan-tage is exploited by sticking and following— nian or niansui —and thus eventually advancing back in a decisive counterattack. (Taken together, as we will see in Chapter 3 , this sequence describes shi , the strategy of wuwei .)

The competition is a subtle interplay of delusive complementary—not opposing—forces between opponents, between hard and soft, each seeking the shrewd strategy of patiently attacking the balance rather than the force, of going right in order to ultimately go deci-sively left.

This is also the insidious strategy of guerilla warfare. While used effectively, for instance, by the scrappy American colonists against the British in the eighteenth century, it was later used deftly against the mighty United States by the far weaker and smaller Vietcong in the twentieth century, the very same alternating intertemporal soft-ness and hardness: When the U.S. troops surged, the Vietcong retreated in a rout into the mountains ( zouhua ), drawing the U.S. troops out until overextended; then the Vietcong counterattacked, following the U.S. troops ( nian ) in a destructive counterrout. The great frustration—the unfairness—is that the harder you push, the harder you fall. Chairman Mao knew these words from the Laozi : “If a small country submits to a great country / It can conquer the great country. Therefore those who would conquer must yield / And those who conquer do so because they yield.” 21 (We will encounter this again with the guerilla warriors of the north in the Epilogue.)

In the wuwei of taijiquan , the advantage comes not from applying force but from circular yielding, from directing the course of events rather than forcing them; from the Laozi , “Hence an unyielding army is destroyed. An unyielding tree breaks.” 22 The patience of the intermedi-ate steps of loss and advantage defeats the impatience of the immedi-ate gain; the direct force is defeated by the counterforce. Thus there are always two games being played in time, one now and one later, against two different opponents. As the great tuishou practitioner Zheng Manqing observed, one must first “learn to invest in loss” by leading “an opponent ’s force away so that it is useless,” and which will “polarize into

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its opposite and be transformed into the greatest profit.” 23 In taijiquan is the essence of The Dao of Capital .

So much of waiting and ignoring present circumstances, of will-ingness to be in an uncomfortable place, is understanding the sequential instead of only seeing the immediate. There is a definite brand of epis-temology at the root of the Laozi . To the Laozi , much of the exterior world is but exterior diversion, much perception is a distraction from a hidden reality—though one which requires diligent attention. It states this most succinctly in “Venture not beyond your doors to know the world / Peer not outside your window to know the way-making. . . . The farther one goes / The less one knows.” 24

Paul Carus, in his definitive 1913 The Canon of Reason and Virtue: Being Lao-tze’s Tao Teh King , went so far as to relate this epistemology of the Laozi to eighteenth-century German philosopher Immanuel Kant: The Laozi “endorses Kant ’s doctrine of the a priori , which means that certain truths can be stated a priori , viz., even before we make an actual experience. It is not the globe trotter who knows mankind, but the thinker. In order to know the sun ’s chemical composition we need not go to the sun; we can analyze the sun ’s light by spectrum analysis. We need not stretch a tape line to the moon to measure its distance from the earth, we can calculate it by the methods of an a priori science (trigonometry).” 25

Indeed, there is an almost antiempirical vein to the Laozi , a stand against the positivist view of knowledge as exclusively flowing from sense perceptions. As Jacob Needleman interprets the Laozi , “We see only things, entities, events; we do not directly experience the forces and laws that govern nature.” 26 Similarly, Ellen Chen says the Laozi “is not pro-science in spirit,” “repudiating the knowledge of the many as not conducive to the knowledge of the one” 27 (thus invalidating induction ). Truth is learned from understanding basic natural and logical construc-tions, a tree that bends to the force of a wind, pent-up water that eventu-ally destroys all in its path, the interplay between snake and bird. There is much deception in appearance, the tyranny of the senses, of empirical data—wisdom that gains particular context and meaning in investing.

INTO THE PIT

My exposure to investing came quite by accident. As a 16-year-old (whose only previous experience with markets was through a share in

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the Rochester Red Wings minor league baseball team, passed down proudly for three generations) I tagged along with my father when he paid a visit to his good friend (and corn futures trader, whatever that was) Everett Klipp at the Chicago Board of Trade. I stood in the visitors’ gallery overlooking the grain trading pits, gaining a bird ’s-eye view over a kaleidoscope of bright trading jackets, flailing arms, and lurching bodies. I was expecting some kind of swanky casino (perhaps out of a James Bond film), but this was different than that. I was mesmerized. It reminded me of watching a flock of birds, a cloud of countless individual parts appearing as a single fuzzy organism, seemingly resting, hovering in midair, until something unseen starts to ripple through it like a pulse of energy, causing a sudden jolting turn in a burst of speed. The flock swoops and dives, rests, and then rises again, with a mechanical yet organic coordination and precision, while the outside observer can only marvel at its driver. In the pit was the same mystery, with pauses interrupted by sudden cascades of noise and energy driven by something imperceptible. It was a financial Sturm und Drang , but within it was an unmistakable, intricate communication and synchronization. In an instant, I scrapped my hard-won Juilliard plans (needless to say, my mother was horrified) and wanted nothing more than to be a pit trader.

After that fateful trip, I became obsessed with the grain futures markets. Price charts soon lined my bedroom walls and I constructed a potted corn and soybean plant laboratory (with seedlings lifted from local farms in the dark of night) for monitoring rainfall and crop prog-ress. From then on, whenever I would see Klipp I always peppered him with questions (often with handy graphs and USDA reports in tow) on price trends, world grain supplies, Soviet demand, Midwest weather patterns—basically on where the markets were headed. His response was always a variation on: “The market is a completely subjective thing, it can do anything. And it is always right, yet always wrong!” His abject disdain for data and information left me bemused, even skeptical of this stubborn old Chicago grain man with the gravelly voice, ever speak-ing in fortune-cookie prose. How could he have done so well as a speculator without knowing—or even caring—where the market was heading? How could it be that “guys who know where the market is heading are no longer at the Board of Trade. They are either retired or broke. And I can ’t think of any that are retired.” Classic Klipp.

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If trading wasn ’t about predicting price movements, then what was it all about? After all, profiting was buying (or selling) at one price and then eventually selling (or buying) it back at a higher (or lower) price. How could this be done without any ability to forecast? The answer, which took this teenager some time to understand, was that the edge to pit trading was in the order flow—the succession of mini-routs , as I always called them—and in the discipline; it was in a patient response to someone else ’s impatience, someone else ’s urgency. The edge was a process— an intertemporal process —an intermediate step to gain an advan-tage, rather than any direct analytical acumen or information. And its monetization—its roundabout production—required time.

The bond pit was where the real action was (and where the aver-age trader ’s age was perhaps twenty to thirty years below that in the corn pit). When it came time to ask Klipp what to study in college to best prepare me for a career in the bond pit, he advised, “Anything that won ’t make you think you know too much” (alas, my economics major would have to remain a dirty secret). During summers and over holiday breaks from college (where I can recall always carrying around a copy of the book The Treasury Bond Basis , still stubbornly trying to ready myself for trading) I worked as a lowly clerk for a few of Klipp ’s traders. Finally, after graduating, with backing from Gramma Spitznagel (my first and best investor) I leased a membership at the Chicago Board of Trade and took my place in the bond pit where, at age 22, I became its youngest trader.

The deliverable instrument of the bond futures contract is the 30-year U.S. Treasury bond (or a nearby “cheapest to deliver”), the benchmark interest rate (along with the 10-year) on which long-term debt is based. In the early-1990s, the bond futures pit was the center of the financial universe, the most actively traded contract and the locus of open outcry in all the world. The pit was where anyone with long-term dollar-denominated interest rate risk in the future converged to hedge their rates, whether savers worried about forward rates falling or borrowers concerned about forward rates rising.

Trading pits are configured like concentric rings (octagons, actu-ally) that descend like a staircase, resembling an inverted tiered wedding cake. The very top, outer step of the bond pit was occupied by the big-gest and baddest traders (as this was where the biggest brokers with the biggest order flow stood, as well as where the best sight lines were into

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the pit—an incalculable advantage). In my first month, I was decidedly not there. In fact, I was at the other extreme, at the very bottom of the pit where only the back month contracts sporadically traded.

For the first month or so, my day started and ended with Klipp standing next to me, feeding me trades and testing to see how I man-aged them. Klipp made it perfectly clear: “You ’re not here to make money, you ’re here to learn how to trade. If you could walk into the pit to make money, you wouldn ’t even be in here. You ’d be in a long line all the way down LaSalle Street, still waiting to get in.” This was an imminently roundabout start down a roundabout path.

THE PRIVILEGES OF A TRADER

Klipp ’s methodology was exceedingly simple—almost dubiously so—conveyed as a parent would to a child, not as principles, but as privi-leges: “As a pit trader, you have two privileges and two privileges only: One, you can demand the edge—buy at the bid price, sell at offer price; two, you can give up that edge when you ’ve made a mistake.”

The “edge” of Klipp ’s allotted privileges is that of the market mak-ers, known as “locals” at the Chicago Board of Trade. (The bond pit was occupied by both locals, virtually all of whom, like me, traded indepen-dently for their own accounts, and brokers, whose job was to execute orders on their clients’ behalf.) What locals do is provide immediacy to those who demand it, meaning they offer prices (a bid price and an ask price) at which they are willing to transact immediately, and in so doing they provide immediate liquidity. In exchange, the locals require a price concession, reflected in their bid and ask prices, a profit they expect to monetize as demands for immediacy flow in from both sides, from buy-ers as well as sellers. Locals stand in the pit all day waiting for that flow, specifically to trade against an impatient counterparty. It ’s not up to the locals to determine when they trade; rather, they wait and, if necessary, wait some more.

The price concessions, the “rents” extracted from urgent counter-parties (who pay for not having to wait), are the local ’s ultimate edge. But, upon receiving such a price concession, the local ’s game is not over; he has the advantage, but he must act yet again, either by stepping aside (taking his loss) or following the market back. He accumulates

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inventory (a position) by transacting against urgent order flow, with the intention of closing out of that inventory profitably once the urgency subsides; thus, advancing seems to be receding, and the local advances by retreating. But, naturally, between these two steps is the potential for great loss—the cost of waiting and holding inventory. So the sooner he gets out the better, but in so doing his aim is to transact better than his urgent counterparty, from whom he received his position in the first place. The late legendary bond local Charlie DeFrancesca (“Charlie D.”) put it best: “The question is: Can you be more efficient than the market?” 28

Klipp liked to think about the local ’s role in more standard business terms, such as the inventory markup of the wholesaler or the retailer, or, more generally, the price spreads that exist in different phases of production for any economic good (including futures contracts). Both involve exploiting intertemporal imbalances between raw material and output, providing immediacy to end users, and the intermediation of waiting, carrying intermediate inventory (including capital goods and other factors of production), and providing a final good at just the right time and place (and, as we will see in Chapter 5 , the more roundabout this process, typically the greater these spreads).

The second allotted privilege was “cruel,” as Klipp would say, because it meant immediately closing out a trade once it turned nega-tive (a “mistake”), what he called “always taking a one-tick loss.” One could expect this to happen roughly half of the time, and much of the other half of the time (depending, of course, on how quickly any prof-its were grabbed, as we ’ll discuss) the price would find its way back to show a loss even then as well.

For instance, if the market was three bid, four offered (meaning 115 and 23/32nds bid, offered at 115 and 24/32nd), I had to buy at three or sell at four—“demand the edge”—without exception. If I managed to buy a one-lot (or one contract) at three, and then a big sell order came in and pushed the market down one tick to two bid, three offered, I was expected to immediately sell that one-lot to someone at two (“give up the edge,” or “step out,” preferably to a broker who would later return the favor), thus taking my one-tick loss (which amounted to $31.25 on one $100,000 bond contract). I was officially in Klipp ’s Alpha School of Trading , as everyone called it, after the name of his firm, Alpha Futures. (We were the guys in the aqua jackets who loved to lose money.)

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Who could argue with this logic? If, as Klipp said, “There ’s only one thing that can hurt a trader at the Chicago Board of Trade, and that ’s a big loss,” then, for God ’s sake, “never take a big loss.” As his own mentor said to him some 40 years before, “Any time you can take a loss, do it, and you will always be at the Chicago Board of Trade.” (To which Klipp always added with a smile, “Well, I ’ve been losing money since 1954, but he was right, I ’m still at the Chicago Board of Trade.”) Naturally, this meant taking many small losses. Hence you had to “love to lose money,” otherwise you ’d just stop doing it.

Impatience and intolerance for many such small losses, as well as urgency for immediate profits, Klipp believed, dealt a death blow to traders, an easy and common one. The well-known disposition effect in finance, an observation that goes back at least a century, states that peo-ple naturally fall victim to these tendencies, and thus do the opposite of Klipp ’s approach: We sweat through large losses and take small profits quickly. Going for the immediate gain feels so right, while taking the immediate loss feels so wrong. The pressing need for consistent and immediate profits is hardwired into our brains; we humans have a shal-low depth of field (as we will see in Chapter 6 ).

And nothing is better at amplifying this natural humanness about us than trading too big and having excessive carrying costs. These are the great external magnifying lenses on the immediate. All is decisive when all is at stake, whether through an excessive loss (because of too much leverage)—a loss that you can ’t afford to take immediately—or an insufficient gain (because of too much debt). No one trade need ever be decisive. As Klipp said, “One trade can ruin your day. One trade can ruin your week. One trade can ruin your month. One trade can ruin your year. One trade can ruin your career!”

It is not surprising, then, that Klipp ’s approach was not embraced by everyone, even by most; in fact, in many ways he was pit trading ’s great-est dissident (despite his title, bestowed by the futures industry, of The Babe Ruth of the Chicago Board of Trade ). Among his greatest critics was none other than Charlie D.—the misinterpretation of whose criticism surely cost many an aspiring Charlie D. his shirt. (There will only ever be one Charlie D.) It was nearly impossible to follow and practice con-sistently—“brutal” was Klipp ’s term to describe the formidable chal-lenge of looking beyond the immediate outcome—of retaining depth of field —a challenge that Klipp believed was essential to gaining an edge.

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This was as it should be; indeed, if everyone accepted Klipp ’s Paradox, it would no longer be effective, no longer even be a paradox. From the Laozi , “The bright path seems dim / Going forward seems like retreat / The easy way seems hard / The highest Virtue seems empty.” 29 Here are the favorite Daoist images of water and the valley, the Laozi ’s “attitude of lowliness,” 30 which water always seeks.

This was Klipp ’s roundabout approach, and that of his mentor and perhaps his before: Expect to lose first, the first loss is a good loss; from that comes greater gain later. Call it playing good defense, embracing loss, biding one ’s time and using the present moment for later advan-tage, the advantage of then playing more effective offense. Or, as Klipp called it, “looking like a jerk, feeling like a jerk.” Waiting must precede opportune action, by definition. Exploiting others’ immediacy was the logic of the roundabout approach, the fundamental edge—the ultimate edge of trading and investing.

In baseball the difference between minor leaguer and major leaguer is generally thought to be in hitting the curve ball, as opposed to just a linearly extrapolated fast ball, and so too is the difference in invest-ing in playing the curve, the roundabout intertemporal bends which deviate from the straight course. My mantra has always been like that of Milwaukee Braves pitcher Lew Burdette, who once said, “I earn my living from the hungriness of hitters.” 31 I earn my living from the hun-griness of investors, from their decisiveness, their forcefulness, from their great urge for immediacy. And this immediacy was not just the bid-ask spread; it was even more so, as we will see, in the larger routs.

ROBINSON CRUSOE IN THE BOND PIT

After about a month, Klipp released me into the wilds of the active bond contract, the upper steps. The discipline had to remain the same—I still had but two privileges—and, like a hawk, he kept an eye on me in the pit as well as on my daily trading statements, to make sure that it did.

The king of the bond pit, nay of all pits, was (and will forever be) Lucian Thomas Baldwin III (trading badge “BAL”), known for the larg-est trading size of any local—thousands of contracts a day—and his ability to single-handedly bully what was then the half-trillion-dollar government bond market. While I was still a teenager, at a time when

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