Risk Perspectives

7/31/2019 Risk Perspectives

1/11

Risk perspectives: What is risk? Its measurement,dimensions, modeling (asset classes, risk factorsand regimes)

By Peter Benedek- http://retirementaction.com/

In a nutshell

After getting walloped twice in a decade with massive market crashes, suddenlyeverybody is interested in the subject of risk. Youll find below a collection ofperspectives on risk: what it is and attempts at measuring and modeling risk, so

we can ultimately try to manage it. What this blog discusses are the challenges

associated with defining measuring and modeling risk. (This is not intended to bea definitive work on risk, rather just view of the considerations and difficultiesassociated with the topic. In a follow-on blog, well try to look at some basic riskmanagement techniques.)

What is risk?

Frank Knight in his 1921 book Risk, Uncertainty and Profit writes that topreserve the difference between a measurable uncertainty and an un-measurable

one we may use the term risk to designate the former and the termuncertainty for the latter.We can also employ the terms objective andsubjective probability to designate to designate the risk and uncertaintyrespectivelythe practical difference between the two categories, risk anduncertainty, is that in the former the distribution of the outcome in a group ofinstances is known (either through calculation a priori or from statistics of pastexperience), while in the case of uncertainty this is not true, the reason being ingeneral that it is impossible to form a group of instances, because the situationdealt with is in a high degree unique. So, objective probability (risk) might be theprobability of getting a head in a coin flip, while subjective probability(uncertainty) might be the probability, predicted in April 2011, of getting aCategory 3 or higher hurricane in Miami during the June-November 2011hurricane season.

Risk, uncertainty and Black Swans
http://retirementaction.com/http://www.amazon.com/Uncertainty-Profit-Frank-Hyneman-Knight/dp/1163518441http://retirementaction.com/http://www.amazon.com/Uncertainty-Profit-Frank-Hyneman-Knight/dp/1163518441


2/11

The simplest and perhaps the most meaningful definition of financial risk mightbe the probability of not being able to meet your objectives (e.g. your monthlyexpenses, or retire at your planned age in your planned lifestyle, etc). So financialrisk is not some measure of what the market will do, but the impact of what themarket will do on your objectives.

Yet one of the most common definitions of market risk is volatility (standarddeviation if return can be represented by a normal distribution or Bell curve),

which happens to be a measure of risk (see below). This is also happens to be oneof the least meaningful definitions of risk to the average investor.

Another definition of risk is mentioned in a recent WSJ article discussing riskentitled How now, 36,000 Dow? The ominous undertone of rallies in whichJason Zweig writes that: Economists contend that riskier assets must offerhigher returns, or no one would invest in them. That is a fallacy, says Howard

Marks, chairman of Oaktree CapitalRiskier assets dont necessarily offer higherreturns, Mr. Marks says; they only appear to do so. Its really simple, he says.If risky investments could be counted on for higher returns, then they wouldnt

be risky. And if investments werent risky, then they probably wouldnt appear topromise higher returns. But by Mr. Markss common-sense definition of riskthe likelihood of losing moneyrising prices are pure investment poison. Thehigher and faster prices go up, the farther and harder they have to fallMeanwhile, cash is moving out of municipal bonds and emerging-markets stocksas their prices fall. If that keeps up, they will get less risky, not moreand more

attractive, not less.

And then an allegorical description of risk as told by Kenneth French, of Famaand French fame, by means of a story about travelling to NYC. You have thechoice a long, winding, smooth but slow road which gets you the in a long time,or you can take a short and bumpy road which is full of pot-holes which could get

you there much more quickly. Then risk means that you not only have to live withthe rough ride of the bumpy road, but also with the possibility that your car might

break down in one of those pot-holes and youll never get to NYC!

Measures of risk?

The most commonly used definition of portfolio/market risk is volatility, which isa statistical measure (the standard deviation-SD) of the variability of returnaround its average value. The simplest ways to explain volatility is that if returns

behaved as normally distributed random variables with average of say 10% andstandard deviation of 20%, then there is a 68%, 95% and 99.7% chance that thereturn (R) will be within 1 SD (i.e. -10%< R


3/11

As indicated in the previous What is risk? section, volatility (standarddeviation) is not only one of the most widely used and perhaps the leastmeaningful definitions of risk to the average investor. Volatility is not that useful

because it is not that intuitive for most investors, and even for whom it has somemeaning (e.g. the probability of being some number of standard deviation fromthe mean) is only meaningful if you assume that returns are normally distributed(a stretch at best). Furthermore the traditional volatility measure (standarddeviation) doesnt differentiate between unfavourable changes or decreases to

your wealth/assets (which youd be concerned about) and favourable changes orincreases in assets (which you are not concerned about). Volatility at best is a

very narrow definition of risk, and at worst it is misleading and/or irrelevant.

Some workers in the field tried to find ways to discriminate between good andbad variability by using downside risk measures such semi-variance (whichonly counts negative variability from expected return in the variance calculation)

or MDD (maximum draw down over a period of interest.

You no doubt have heard the oft-quoted message that the risk of equitiesdecreases dramatically if you have a very long holding period. Thosemathematically inclined will readily resonate with the reason for perceiveddecreased risk of stock over longer holding period is the use of standard deviation(SD) as a measure of risk. To show that the risk actually decreases with time, ifthe SD over one period is SD(1), then over n-period is SD(n)= SD(1)/SQRT(n).Therefore if risk or SD=20% per year then the predicted SD over 25 years is SD

(25) = SD (1)/SQRT (25) =20/5=4 or a dramatic decrease in predicted risk fromSD=20% to SD=4%! This concept that time reduces or eliminates risk is referredto as time diversification, but it is only a myth (e.g. see my Time Diversification

blog.)

A somewhat different measure of risk which is a measure of intra-horizon risk isfirst passage volatility, defined as the likelihood of a certain loss over ourplanning horizon. This measure perhaps a little more realistic and we should beable to better relate to since it immediately leads to the question of how wed deal

with such a drop in the value of the portfolio at any point over the horizon ofinterest. Note, that this first passage volatility measure of risk actually increasesover time as opposed to the traditional definition of volatility which decreasesover time!(Bartolomeo). (Later on well also discuss Kritzmans used ofturbulence (and risk regimes) and first passage probability to better assessrisk of a portfolio.)


4/11

Further putting doubt on the value of Volatility (standard deviation) as a riskmeasure, Pablo Triana in the Financial Times Challenging the notion that

volatility equals riskwants to dispel the notion that volatility is a good indicatorof risk. He argues (the obvious, at least in retrospect) that volatility can providecamouflage for lethal assets, given how easy it is to cook the numbers by simplygoing back a few more years and adding them if they were a period of good

behaviour; this and other similar tricks mentioned indicate that it is quite easyto use standard deviation to categorize problematic stuff as non-problematic.

Returning to the perhaps simplest statement of risk The likelihood of not beingable to meet ones objectives, consider a financial planning situation whichdemonstrates the complications of even this simple definition. A commonapproach in financial planning is to evaluate the risk associated with some

withdrawal level in retirement is to use a Monte Carlo simulation to estimate the

probability of running out of money for some asset allocation and expected yearsin retirement. In a Russell research paper entitled Mis-measurement of risk infinancial planning Richard Fullmer CFA argues that this measure of running outof money is an inadequate measure.

He suggests that in general a better risk measure is the product of the probabilityof failure (i.e. unfavourable event or outcome) and magnitude of loss, i.e. Risk=Probability * Magnitude. However, in the context of financial planning aneven better measure might be Shortfall Risk= Probability of Shortfall *

Magnitude of Shortfall, i.e. it is not just the probability that a failure occurs(i.e. you run out of money) that counts, but scenarios with smaller averageconditional magnitude of shortfall or cases where failure is occurring closer tothe end of a 30 year retirement plan are less undesirable (or are more desirable)than when failure occurs many years before projected time in retirement.

So now we can go back to our earlier comment that the simplest and perhaps themost meaningful definition of (market) risk might be the probability of not beingable to meet your objectives (e.g. unable to meet your monthly expenses, orretire at your planned age in your planned lifestyle, etc). So (market or some)event risk is not some measure of what the variability that is associated with the(market or some) event, but the impact of that event and associated variability

will have on your objectives. As the saying goes, stuff happens, so whats theimpact of that stuff on your objectives?
http://www.ft.com/cms/s/1caddd3c-b783-11df-8ef6-00144feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms%2Fs%2F0%2F1caddd3c-b783-11df-8ef6-00144feabdc0%2Cs01%3D1.html&_i_referer=http%3A%2F%2Fretirementaction.com%2F2012%2F03%2F02%2Frisk-http://www.ft.com/cms/s/1caddd3c-b783-11df-8ef6-00144feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms%2Fs%2F0%2F1caddd3c-b783-11df-8ef6-00144feabdc0%2Cs01%3D1.html&_i_referer=http%3A%2F%2Fretirementaction.com%2F2012%2F03%2F02%2Frisk-http://www.ft.com/cms/s/1caddd3c-b783-11df-8ef6-00144feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms%2Fs%2F0%2F1caddd3c-b783-11df-8ef6-00144feabdc0%2Cs01%3D1.html&_i_referer=http%3A%2F%2Fretirementaction.com%2F2012%2F03%2F02%2Frisk-http://www.plansponsor.com/uploadfiles/Russell.pdfhttp://www.plansponsor.com/uploadfiles/Russell.pdfhttp://www.ft.com/cms/s/1caddd3c-b783-11df-8ef6-00144feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms%2Fs%2F0%2F1caddd3c-b783-11df-8ef6-00144feabdc0%2Cs01%3D1.html&_i_referer=http%3A%2F%2Fretirementaction.com%2F2012%2F03%2F02%2Frisk-http://www.ft.com/cms/s/1caddd3c-b783-11df-8ef6-00144feabdc0,Authorised=false.html?_i_location=http%3A%2F%2Fwww.ft.com%2Fcms%2Fs%2F0%2F1caddd3c-b783-11df-8ef6-00144feabdc0%2Cs01%3D1.html&_i_referer=http%3A%2F%2Fretirementaction.com%2F2012%2F03%2F02%2Frisk-http://www.plansponsor.com/uploadfiles/Russell.pdfhttp://www.plansponsor.com/uploadfiles/Russell.pdf


5/11

Dimensions of risk

When investors think of risk, they most commonly think about market risk. Butinvestment/market risk is just one dimension of risk, which may not even be themost significant type of risk threatening an individual (depending on where theyare in their life-cycle. From a life-cycle investing perspective:

TC = FC + HC i.e. Total Capital (TC) = Financial Capital (FC) + Human Capital(HC) where HC is the present value of ones remaining lifetime work income.

Typically, FC=0% (or close to it) at start of ones working life, while HCrepresents (close to) 100% of a persons TC. At retirement the situation is exactlyreversed. So typically at start of ones working life market risk is a relatively

unimportant dimension of risk compared risk of death or disability. Whereas atretirement, if one is living exclusively off ones portfolio then market, longevityand inflation risks might be dominant dimensions (and death and disability arefinancially less important).

In an old blog based primarily on Zvi Bodies writings on Life-Cycle Investing Idiscuss some of the major risks one faces through ones life-cycle:

- disability (initially most wealth is HC, so loss of earning ability can be

disastrous) death (with young family/dependents, death of primarybreadwinner can lead to poverty) investment/market (especially near the startof de-accumulation, when volatility around retirement can result in significantreduction in retirement income and/or delay in the start date of retirement)(There is a long list of (sub-)risks associated with investment/market risk suchas: currency risk, credit risk, default risk, interest rate risketc) longevity(not only are people retiring earlier, but life expectancy has increased to 19 and 12

years, for 65 and 75 year olds, respectively, and is growing; of course about 50%of individuals live past the indicated life expectancy. For a 65 year old couple,there is about a 50%, 25% and 10% probability to one of them living to 90, 95 and100, respectively). The net effect is that people are spending more time inretirement and theyll need an income stream over a longer retirement period

before exhausting their assets. -inflation (this is a scourge throughout the life-cycle, but it especially severe during retirement, eating away at your predominantfinancial capital). Just as inflation is particularly corrosive for older/retiredpeople, deflation is more damaging for young/working people (e.g. they have torepay their mortgage with more valuable dollars).


6/11

Other related risks that come to mind are:

-are you saving enough?

-if you annuitize, are you annuitizing at the right time(interest rate risk, mortalitycredits, costs/fees)?

-are you being overly conservative with your investments? (e.g. little or noequities in your portfolio may lead to not being able to keep up with inflation).

-are you considering Black Swan events (and tail risk) (i.e. unknown unknowns)?

Risk modeling

As mentioned earlier the most commonly discussed definition of risk is volatility(the standard deviation of return per unit of time, say a year), and assuming thatthe distribution of returns is normal around the mean long-term return of themarket (e.g. stock market). Also mentioned earlier was that this is a slipperyslope, since mathematics will quickly lead you to incorrectly conclude that stocksare riskless in the long-term. Unfortunately, even if the return distributions werenormal (which they are not), youd have to contend with intra-horizon risk; i.e. inany year between 1 to N you could encounter one of those recently observed

undesirable periods like the fall-winter of 2008 when we took a 40-70% hitdepending on which market we were invested in.

There is a big difference between modeling physical behaviour (as in the scienceof physics applicable to inanimate objects) as opposed to economic behaviour(which involves humans with their aspirations, plans, fears, greed and theuncertainties/surprises that nature throws before us.)

John Kay writes in the Financial Times Dont blame luck when your modelsmisfire that The source of most extreme outcomes is not the fulfilment ofpossible but improbable predictions within models, but events that are outsidethe scope of these models There are no 99 per cent probabilities in the real

world. Very high and very low probabilities are artifices of models, and theprobability that any model perfectly describes the world is much less than one.Once you compound the probabilities delivered by the model with the unknown

but large probability of model failure, the reassurance you crave disappearsInsurance companies do fail, but not for the reasons described in such models.They fail because of events that were unanticipated or ignoredthe search forobjective means of controlling risks that can reliably be monitored externally is as

fruitless as the quest to turn base metal into gold. Like the alchemists and thequacks, the risk modellers have created an industry whose intense technicaldebates with each other lead gullible outsiders to believe that this is a profession

with genuine expertise.
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7/11

We will succeed in managing financial risk better only when we come torecognise the limitations of formal modelling. (My emphasis) Control of risk isalmost entirely a matter of management competence, well-crafted incentives,robust structures and systems, and simplicity and transparency of design.

So keeping in mind the difference between modelling physical and economicbehaviour, the difficulty to build credible models which then are furtherchallenged by the use of parameters that change over time and the impossibilityto a priori model Black Swan events (by definition), you must take financial riskmodels (even when packaged with sophisticated analysis by brilliant individuals

back up by enormous computing power) with a large grain of salt! I like toremind myself periodically of Richard Hammings warning that computing is forinsight, not numbers. So given these caveats, we can now consider some of risk

models that (re-)emerged post-Great recession of 2008/9: (1) multi-regimes vs.one risk regime and (2) risk factors rather than asset classes as the analysiselements (and building blocks) rather than asset classes.

Risk regimes

In the search for new ways to tackle policy portfolios (after the perceived failureof the models previously used) based on the assumption that market behaviour

can be adequately described as a normal random variable, many have suggestedthe need to perhaps think of the market as having multi-regimes rather than justa single-regime.

For example in the Blackrock/iShares paper The new policy portfolio Dopfelargued that perhaps The wide dispersion can be explained by the presence ofeconomic and financial market regimesboth good and bad. Each regime hasdistinct asset class assumptions, represented by higher or lower expected returnsand volatilities and then looked at the implications on the (institutional orindividuals) portfolio. In each regime (good, bad and transitions), asset classes

would have different characteristics. The paper demonstrates how fat-tails andskewness can be modelled using the sum of two normal distributions (the sum isnot normal). The model includes good and bad states and transitions (good-to-

bad and bad-to-good).The proposed models allow investors to assess theirportfolio outcomes using a more realistic model and could result in new policyportfolios. This is an interesting paper which also includes mechanisms howinvestors might use the expectation a multi-regime environment to assess theirportfolio outcomes using a more realistic model and how to create new policyportfolio.
https://www2.blackrock.com/webcore/litService/search/getDocument.seam?venue=PUB_INS&source=CONTENT&contentId=1111097827https://www2.blackrock.com/webcore/litService/search/getDocument.seam?venue=PUB_INS&source=CONTENT&contentId=1111097827


8/11

On the same topic of unsuitability of a normally distributed representation of asingle risk regime, the article State Street identifies new approaches to managingportfolio risk examines the changing views of traditional practices andidentifies new techniques and investment strategies that focus on measures ofmarket turbulence, risk, liquidity and diversification Non-normal investmentreturns and dramatic swings in valuation may occur more frequently in coming

years, the report states. Consequently, investors should give new considerationto within-horizon risk, investment regimes and turbulence. Increasingly,investors are turning to regime-specific risk analysis to form a more completepicture of portfolio risk. Their more detailed article Rethinking asset allocationState Street argues that we know that the normality assumption as well as thestability of standard deviations and correlations cannot be relied upon over time,so they suggest that investors disaggregate historical returns derived from

normal periods and those associated with periods of market turbulence.

The paper also warns against disregarding within horizon risk for which investormust understand their liquidity requirements and liability schedules (i.e. could

you continue to pay your bills and live in the lifestyle that youre accustomed to ifthe market crashed during your and/or your spouses retirement?). The paperalso addresses the universally accepted precept of diversification. Yet mostportfolios demonstrate asymmetrical correlation, with returns more diversified(i.e. uncorrelated) on the upside and considerably less (diversified, i.e. more

correlated) on the downside- precisely the opposite of what most investors areseeking. Therefore the article suggests that when sentiment is positive we shouldincrease our allocation to risky assets, but when sentiment turns negative oneshould reallocate to fixed-income and cash instruments (if we only knew how todo that little market timing.) Also discussed is the importance of rebalancing, butthe article points to the difficulty of doing that when the market stresses arepresent; as a solution at times of high volatility and problematic liquidity,overlay strategies are suggested whereby cash balances are equitized by usingindex futures. Tolerance-band rebalancing is preferred to calendar-basedrebalancing, so long as the bands are selected to be appropriate for the portfolio.Turbulence is a statistical measure designed to identify periods of unusualfinancial returns- either in terms of volatility or correlation, or bothperiods ofextraordinarily high returns could be considered just as turbulent as those of amarket collapse. Averaging correlations and standard deviations withoutseparating out the different regimes that were involved can yield meaninglessresults.
http://www.hedgeweek.com/2010/08/02/56707/state-street-identifies-new-approaches-managing-portfolio-riskshttp://www.hedgeweek.com/2010/08/02/56707/state-street-identifies-new-approaches-managing-portfolio-riskshttp://www.fwalliance.com/whitepapers/SSGA%20-%20Rethinking_Asset_Allocation_6.30.10.pdfhttp://www.hedgeweek.com/2010/08/02/56707/state-street-identifies-new-approaches-managing-portfolio-riskshttp://www.hedgeweek.com/2010/08/02/56707/state-street-identifies-new-approaches-managing-portfolio-riskshttp://www.fwalliance.com/whitepapers/SSGA%20-%20Rethinking_Asset_Allocation_6.30.10.pdf


9/11

And speaking of turbulence and multi-regimes, Kritzman in Long livequantitative models argues that The flaw lies not in the models but in the wayless-than-careful investor implement them and then proceeds to explain howmeasures of turbulence and first passage probability would have predicted

VaR (Value-at-Risk is a measure of the largest loss over some period of time withsome probability (e.g. 95% or 99% of the time, i.e. 5% or 1% of the time the lossmay be greater) of 35.1% (rather than 9.9% estimated naively; VaR is used mostly

by large institutions to manage their overall risk, but it was not very effectmeasure in the 2008-2009 crash as we found out), and in fact cumulative lossduring the crisis was 29.4% and maximum drawdown was 35.5%, for a portfolioof 35% U.S. stocks, 24% foreign stocks, 33% U.S. bonds, 3% real estate and 3%commodities.

Risk factors

Pimcos Page and Taborsky in The myth of diversification: Risk factors vs. assetclasses observe that diversification often disappears when you need it most.The example they give is the correlation of the Russell 3000 and the MSCI WorldEx-U.S. indexes between 1970 and February 2008 had a correlation of -17%; incontrast when both markets were down more than one standard deviation, thecorrelation between them was +76%. They indicate that generally the economy

oscillates between two regimes: risk on (a panic driven, high volatility statecharacterized by economic contraction) and risk off (a steady, low volatilitystate characterized by economic growth). Pimco believes asset class returns aredriven by common risk factors, and risk factor returns are highly regime specific.So risk factors should be the building blocks since they are the independent

variables which in turn drive the behaviour of asset classes. Their analysisshowed that correlations across risk factors were lower than across asset classesand that the average correlation across risk factors did not increase duringmarket turbulence. Regimes are defined by market turbulence which isdefined in terms of volatility and correlations (which coincide with and easier toidentify by asset class returns). Interestingly both their risk factors and assetclasses contained equities, real estate, commodities. However in asset classes

we get US small cap, US large cap, global, and emerging markets, and bonds asasset classes.; whereas risk factors included equity, size, value, momentum and

bonds were represented by their characteristics like duration, 2-10 slope, 10-30slope, EM spread, mortgage spread, corporate spread, swap spread. A majorityof investors dont think twice before they average their risk exposures acrossquiet and turbulent regimes. Consequently much of the time, investors portfoliosare suboptimal.
http://viewer.zmags.com/publication/d42aa7ee?page=34#/d42aa7ee/10http://viewer.zmags.com/publication/d42aa7ee?page=34#/d42aa7ee/10http://www.pimco.com/EN/Insights/Pages/TheMythofDiversificationRiskFactorsvsAssetClasses.aspxhttp://www.pimco.com/EN/Insights/Pages/TheMythofDiversificationRiskFactorsvsAssetClasses.aspxhttp://viewer.zmags.com/publication/d42aa7ee?page=34#/d42aa7ee/10http://viewer.zmags.com/publication/d42aa7ee?page=34#/d42aa7ee/10http://www.pimco.com/EN/Insights/Pages/TheMythofDiversificationRiskFactorsvsAssetClasses.aspxhttp://www.pimco.com/EN/Insights/Pages/TheMythofDiversificationRiskFactorsvsAssetClasses.aspx


10/11

The starting point for Knut N. Kjaer in Asset and risk management in a post-crisis market is also risk factors, such as (p.25): real rate, inflation premium,nominal bond premium, credit risk premium, cash-flow risk premium, growthand country risk premium, size/liquidity premium, value/carry, momentum and

volatility. He then argues that it is insufficient for portfolio managers to focusexclusively on asset classes, such as: T-bills, government bonds, emerging market

bonds, corporate bonds, currencies, convertibles, public equity, emerging marketequity, private equity, real estate, infrastructure and commodities. Risk factorsmust be included in portfolio construction for understanding of what is drivingasset class returns. (Kjaer also sings the praises of rebalancing which he calls themost important institutional mechanism a manager can implement to buildinstitutional clarityrebalancing is essential from two perspectives: it providesthe discipline to avoid herd behaviour and pro-cyclical investing, and it exploits

mean-reversions while earning a diversification premium. It ensuresdiversification and mitigates risk. Rebalancing also imparts an automatic value

bias because buying assets with recent price declines and selling assets withprices gains provide liquidity.

In Turbulence can improve portfolio diversification Susan Wiener interviewsMark Kritzman who says that turbulence is a statistical measure of both

volatility and correlation. Volatility alone doesnt capture enough informationabout interactions between assets. Also, he suggests that measures such as VIX

have additional shortcomingsthey are only available for asset classes that haveliquid option markets, and they are forward-looking measures, so they dontmeasure whats actually going on now. He indicates that since turbulencepersists, it may be useful as an early warning signal and a signal to gradually andmove partially out of risky assets since risk adjusted returns drop significantly insuch times. But his (Kritzmans) top priority is not forecasting turbulencebut

building a portfolio that will be more resilient during turbulence. (In anotherarticle Portfolios for turbulent times she discusses the turbulent optimalportfolio is heavily allocated to non-US equities (37%) as well as commodities(12%) and REITs (6%). Time will tell if we truly understand better if risk factorsare superior to asset classes from a downside correlation perspective, becausepractically we dont worry much about upside correlation. Upside and downsidecorrelations are different, so for real diversification we should be looking atdownside correlations (Kritzman)
http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CFQQFjAE&url=http%3A%2F%2Fwww.wertpapier-forum.de%2Findex.php%3Fapp%3Dcore%26module%3Dattach%26section%3Dattach%26attach_id%3D70842&ei=Xb_8T_LMIOSYiAeCpMH4Bg&usg=AFQjCNF9Is94xXB7b6GhyplHcyhttp://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CFQQFjAE&url=http%3A%2F%2Fwww.wertpapier-forum.de%2Findex.php%3Fapp%3Dcore%26module%3Dattach%26section%3Dattach%26attach_id%3D70842&ei=Xb_8T_LMIOSYiAeCpMH4Bg&usg=AFQjCNF9Is94xXB7b6GhyplHcyhttp://www.advisorperspectives.com/newsletters09/pdfs/Turbulence_Can_Improve_Portfolio_Diversification.pdfhttp://www.advisorperspectives.com/newsletters08/Portfolios_for_Turbulent_Times.htmlhttp://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CFQQFjAE&url=http%3A%2F%2Fwww.wertpapier-forum.de%2Findex.php%3Fapp%3Dcore%26module%3Dattach%26section%3Dattach%26attach_id%3D70842&ei=Xb_8T_LMIOSYiAeCpMH4Bg&usg=AFQjCNF9Is94xXB7b6GhyplHcyhttp://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CFQQFjAE&url=http%3A%2F%2Fwww.wertpapier-forum.de%2Findex.php%3Fapp%3Dcore%26module%3Dattach%26section%3Dattach%26attach_id%3D70842&ei=Xb_8T_LMIOSYiAeCpMH4Bg&usg=AFQjCNF9Is94xXB7b6GhyplHcyhttp://www.advisorperspectives.com/newsletters09/pdfs/Turbulence_Can_Improve_Portfolio_Diversification.pdfhttp://www.advisorperspectives.com/newsletters08/Portfolios_for_Turbulent_Times.html


11/11

Bottom line

Definitions of risk range from the mathematically convenient but not verymeaningful, to perhaps meaningful but mathematically intractable; forcing one tothink in terms of something simple like not being able to meet ones objectives.So no wonder we have difficulty in measuring risk, given that there is not even aunique definition of what risk is. Volatility doesnt cut it; neither as a definitionnor as a measure of risk. The closest you might come to a meaningful definition isthe probability of something bad (e.g. a shortfall) happening multiplied by thesize of the shortfall. Types of risk range from known-unknowns (measurable risk)to unknown-knowns (un-measurable risk) all the way to unknown-unknowns(Black Swans). Unfortunately, only the known-unknowns category can be reliablymodelled.

So for most risk situations credible models are not available, parameters drivingthem dont behave consistently over time (e.g. returns, standard deviations,correlations), and we are even unsure what might be the appropriateindependent variables to consider (e.g. asset classes or risk factors). Its nosurprise that markets are so difficult to model, since unlike inanimate things for

which physics might be appropriate (but even there not useful, as in hurricanes),behaviour of markets is heavily influenced by human behaviour. Unfortunately,in order to derive predictive value from risk models, you need credible models;and the state of risk modeling is considered by some to be an art and by others

sorcery. Another risk categorization is that based on its dimensions; theseinclude: death, disability, market/investment, inflation, longevity and manyothers. The most relevant dimensions to each individual are a function of oneslife-cycle stage. For younger individuals early in their work careers protection oftheir human capital against death and disability is most important, whereasinflation, longevity and market risk are most important in the near- or in-retirement stage of ones life-cycle, when Financial Capital is predominant.Bottom line is that definition, measurement, modeling or a completeunderstanding of all dimensions of risk can only be described as partial at best,and potentially misleading or wrong at worst.

http://retirementaction.com/2012/03/02/risk-perspectives-what-is-risk-its-measurement-dimensions-modeling-asset-classes-risk-factors-and-regimes/

Reproduced by kind permission of Peter Benedek atRetirementAction.com
http://retirementaction.com/2012/03/02/risk-perspectives-what-is-risk-its-measurement-dimensions-modeling-asset-classes-risk-factors-and-regimes/http://retirementaction.com/2012/03/02/risk-perspectives-what-is-risk-its-measurement-dimensions-modeling-asset-classes-risk-factors-and-regimes/http://retirementaction.com/http://retirementaction.com/2012/03/02/risk-perspectives-what-is-risk-its-measurement-dimensions-modeling-asset-classes-risk-factors-and-regimes/http://retirementaction.com/2012/03/02/risk-perspectives-what-is-risk-its-measurement-dimensions-modeling-asset-classes-risk-factors-and-regimes/http://retirementaction.com/

Risk Perspectives

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