Rethinking Portfolio Construction andRi kM td Risk Management · Diversification based on...

Deutsche Bank AG

Rethinking Portfolio Construction d Ri k M tand Risk Management

January 2012

- A Third Generation in Asset AllocationJanuary 2012

Bradley A. Jones, Ph.DMacro Investment [email protected]

852 2203 8170+852 2203 8170

All prices are those current at the end of the previous trading session unless otherwise indicated. Prices are sourced from local exchanges via Reuters, Bloomberg and other vendors. Data is sourced from Deutsche Bank and subject companies. Deutsche Bank does and seeks to do business with companies g j p pcovered in its research reports. Thus, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MICA(P) 146/04/2011

“Dwell on history and you will lose an eye …

… Ignore history and you will lose both”

- Russian Proverb

Brad Jones; [email protected]; +852 2203 8170 January 2012

Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

1

Contents*

Part I - The Peril of the 60/40 Policy Portfolio (It’s Riskier than You Think)

Part II – From Second to Third Generation Asset Allocation

Concluding Remarks

Appendix I: Building an Investment Defence Against Behavioural Biasespp g g

Appendix II: Noise vs. Signal - the (Non-Linear) Role of Timepp g ( )


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

* This is a summarized version of a paper originally published on November 21, 2011, entitled “Third Generation Asset Allocation”, Brad Jones, Deutsche Bank Global Markets Research.

2

A One Minute Synopsis on Diversification and Robustnessy pBuild Portfolios of Risk Factors and Risk Premia’s, Not Assets

A lack of diversity and failure to adapt to a changing environment have been keyA lack of diversity and failure to adapt to a changing environment have been key contributors to extinction in the animal kingdom. Bacteria are arguably the best exponents of adaptability and diversification – they have existed for 4.5bn years and outlived Dinosaurs by a factor of 24:1Dinosaurs by a factor of 24:1

Like many investment strategies, Dinosaurs were short a regime shift – they were perfectly calibrated to a set of initial conditions but could not cope once the environment changedcalibrated to a set of initial conditions but could not cope once the environment changed

Risk Factors vs. Asset Classes – allocating capital across asset classes and investment styles represents superficial diversification if payoffs are exposed to the same set of risk y p p p y pfactors. Diversification based on underlying risk factors or return sources, not historical correlations over a select sample period plugged into a MV optimizer, should be the building blocks of portfolio construction. Beware a 60/40 equity/bond portfolio is 100% g p q y pexposed to unexpected inflation or sovereign risk, while 14 different HF strategies had their worst ever drawdown in the 2008/09 crisis (all were short systemic liquidity risk)

The only insurance against regime shifts, black swans, the peso problem and drawdowns is to seek out multiple sources of risk premia across a host of asset classes and geographies, designed to harvest different features (value, momentum, illiquidity etc.) of


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

the return generating process, via a large number of small, uncorrelated exposures

3

Three 3-Dimensions of Risk ExposurepBeta Risk Premia, Style Risk Premia and Systemic/Macro Risk

Beta Risk Premia

B d D ti- Bond Duration - Credit Risk Premia- Equity Risk Premia- Commodity Risk Premia- Alternatives

Style Risk Premia Systemic/Macro Risk- Value Premium- Carry Premium- Momentum Premium

- Growth Risk- Inflation Volatility Risk- Liquidity Risk

- Volatility Premium- Illiquidity Premium- Size Premium

q y- Sovereign Risk


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank.

Size Premium

4

Part I.

First Generation Asset Allocation

- The Peril of the 60/40 Policy Portfolio


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

5

1st Generation Asset Allocation – the 60/40 Policy PortfolioyThe Underlying Assumptions …

Rebalancing back to fixed weights constitutes the best form of risk management as it imparts a value bias in an otherwise efficient and unpredictable world

Markets are largely efficient – returns are distributed randomly over time, regime dependence and valuation bubbles either don’t exist or cannot be monetized

Active Management has a dubious record (after costs) and the future is unknowable, hence long-term average returns are a reliable guidepost for the future (the 60/40 portfolio in the US has generated a 4% average annual real return back to 1900 i d i d i il d liti l i )1900, a period spanning wars, depressions, currency, oil and political crises)

Stocks and bonds (reliably) diversify one another (ie. correlations are stable)

Intertemporal path dependency risk is vastly subordinate to end-of-horizon wealth and shortfall considerations, so long-term investors can ignore it

BUT - if you were sailing from New York to Bermuda, would you rely only on long-term average weather conditions, with no ability to adjust to deviations from average conditions during the voyage?


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

conditions during the voyage?

6

US Stock, Bond and 60/40 Portfolio Returns Since 1900,At First Glance, Why Worry - the Policy Portfolio has Generated Real Returns of 4% p.a. for More than a Century!

Nominal Bonds Nominal Stocks Nominal 60/ 40 Real Bonds Real Stocks Real 60/ 40

Arithmetic Average Annual ized Returns 4.9% 9.0% 7.3% 1.9% 6.0% 4.3%

Compound Annualized Returns 4.8% 7.8% 6.9% 1.7% 4.7% 3.8%

Standard Deviation of Monthly Returns 4.7% 15.5% 9.6% 5.6% 15.5% 9.8%

Compound Return Per Unit of Volati l ity 1.02 0.50 0.72 0.31 0.31 0.39

Ratio of Downside to Upside Volati l ity 0.97 1.54 1.44 0.88 1.49 1.38

Compound Return Per Unit of Downside Volati l ity 1.27 0.56 0.83 0.47 0.36 0.48

Maximum Drawdown -15% -90% -73% -57% -86% -66%

Length of Maximum Drawdown (Y rs) 3.3 21.3 20.3 45.2 24.9 24.3

Calmar Ratio (Y rs) 3.1 11.5 10.6 32.9 18.2 17.1

% Up Months 80% 63% 65% 57% 60% 61%

Monthly Return Skew 1.2 -0.9 -0.8 0.5 -0.8 -0.6

Monthly Return Kurtosis 10.7 9.3 8.2 5.9 8.7 6.9

% Up Y ears 88% 70% 74% 63% 65% 67%

Best Year 37% 100% 53% 32% 98% 51%

Worst Year -7% -54% -37% -14% -50% -31%

% Time Incurring Negative Real Returns over 10yrs 0% 12% 7% 35% 24% 22%

% Time Incurring Negative Real Returns over 20yrs 0% 5% 1% 32% 13% 9%


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Robert Shiller database. Based on monthly returns since 1900.

7

But All the Returns Were Concentrated in Four Decades… Each of Which is Unrepeatable – the 1920s and ‘50s were Post-War Recoveries, while the 1980s and ‘90s were Windfall Gains

20%20%

Real Stock Returns Real Bond Returns Real Return on 60/40 Policy Portfolio

12.7% 11.7% 11.7%11.3%

10%

15%

10%

15%

6.3%

1 1%

9.1%

4.5%

0 5% 0.7%

5%

10%

5%

10%

-4.7% -2.3%

1.1%

-0.3%

0.5% 0.7%

-5%

0%

-5%

0%

-10%-10%

1900s 1910s 1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990s 2000s Best 4 Other 7 Decades Decades


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Robert Shiller database

8

Long Waves of Feast or Famine are the Rule for Returnsg… Returns Are Regime Dependent, Not Randomly Distributed

12%

Rolling 10yr Compound Annual Real Bond Returns40%

Rolling 10yr Compound Annual Real Stock Returns

6%

8%

10%

12%10yr Rolling Standard Deviation of Returns

20%

30%

40%10yr Rolling Standard Deviation of Returns

2%

0%

2%

4%

0%

10%

20%

-8%

-6%

-4%

-2%

-20%

-10%

1909 1919 1929 1939 1949 1959 1969 1979 1989 1999 2009 1909 1919 1929 1939 1949 1959 1969 1979 1989 1999 2009


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


9

The Risk Characteristics of 60/40 are Stomach-Churningg… Large and Lengthy Drawdowns are Par for the Course

-20%

-10%

0%0

5

20%

-10%

0%Drawdown in Real Portfolio Level (lhs) Years in Drawdown (rhs, inverted)

-50%

-40%

-30%

-36%

-31%-26%

-22%10

15

20

-40%

-30%

-20%

80%

-70%

-60%

Nominal terms Real terms-66%

-56%

20

25

30-70%

-60%

-50%

-80%

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011

3070%

Oct-1929 to Jan-1954

Jul-1911 to Nov-1926

Dec-1968 to Dec-1982

Nov-07 to Today

Sep-2000 to Nov-2004

Oct-1906 to Jul-1909


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


10

The Risk Characteristics of 60/40 are Stomach-Churningg… 60/40 Has Generated Negative Real Returns over a Rolling 10yr Holding Period for Almost a Quarter of the Sample!

40%

Realized Shortfall Probabilities in the US from 1900 - 2011 35%

32%

30%

40%(Shortfall Threshold = 0%)

Rolling 10yr periods Rolling 20yr periods

24% 22%

20%

30%

12%

7%5%

13%

9%10%

0% 0%

5%1%

0%

Nominal Bonds Real Bonds Nominal Stocks Real Stocks Nominal 60/40 Real 60/40Nominal Bonds Real Bonds Nominal Stocks Real Stocks Nominal 60/40 Portfolio

Real 60/40 Portfolio


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


11

The Mean is NOT the Messageg4% Unconditional Average Returns – a Frail Reed to Lean Upon

Annual Real Returns to the 60/40 Portfolio in the US (1900 - 2010)

40%

50%

60%Annual Real Returns to the 60/40 Portfolio in the US (1900 2010)

Long-term Average Returns(Geometric Average of Annualized Monthly Returns = 3.8%),(Arithmetic Average of Annualized Monthly Returns = 4 3%)

20%

30%

40% (Arithmetic Average of Annualized Monthly Returns = 4.3%) (Arithmetic Average of Annual Returns = 5.5%)

-10%

0%

10%

-40%

-30%

-20%

-40%

1 11 21 31 41 51 61 71 81 91 101 111Cumulative Frequency (Years)


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


12

The Mean is NOT the Messageg4% Unconditional Average Returns – a Frail Reed to Lean Upon

Distribution of Real Annual 60/40 Portfolio Returns in the US (1900 - 2010)

24%25%

30%60/40 Portfolio Returns in the US (1900 - 2010)

Real negative returns 1 in 3 years,& real returns worse than -10%

1 in every 6 yrs!

14%

19%

12%15%

20%

1 in every 6 yrs!

10%12%

6% 6%

10%

5%

10%

0%

5%

>15% 10% to 5% to 0 to 5% 0 to -5% -5% to -10% to < -15%15% 10% to 15%

5% to 10%

0 to 5% 0 to 5% 5% to -10%

10% to -15%

15%


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


13

Extreme Time-Variation in Returns is a Global Phenomena… Regime Dependence Matters (not Unconditional Averages)!

Post-WWIIReconstruction Boom

Deregulation & Collapse in Inflation & Bond Yields

9.1%

11.7% 11.7%11.9% 11.5%

8 3%10%

12%

14%Reconstruction Boom Inflation & Bond Yields

4.5% 4.3%

8.3%

4%

6%

8%

Stagflation,

Equity, Housing & Structured Credit

Bubbles Burst

-0.3%

0.5% 0.4%

2%

0%

2%

4%Oil Crises

Bubbles Burst

-3.5%-4%

-2%

1950s 1960s 1970s 1980s 1990s 2000s

US Average Across G8 Excluding US


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


14

Largest Drawdowns to 60/40 Portfolios Around the Worldg… 60/40 is Riskier Than You Think!

00%

Largest Drawdown in Real Terms for 60/40 Portfolio (lhs) Length of Drawdown (in years, rhs inverted)

2

4

630%

-20%

-10%

51%-48% -47%

-43% -41% -40% -40% -40% -38% -38%-34% -34% -34% -31% -31% -30% -29% -28% -27% -26% 6

8

10-50%

-40%

-30%

-65%-59% -58% -58%

-53% -51% 12

14

16-80%

-70%

-60%

-80%18-90%

Gre

ece

rela

nd

un

gary

Au

stri

a

inla

nd

elg

ium

we

de

n

Po

lan

d

rman

y

Ital

y

ort

uga

l

rlan

ds

orw

ay

Jap

an

Fran

ce

h R

ep

.

nm

ark

Spai

n

Me

xico U

S

erl

and

anad

a

stra

lia

eal

and

Afr

ica

UK

G Ir

Hu A Fi Be

Sw P

Ge

r

Po

Ne

the N

o F

Cze

c

De

n M

Swit

ze C

Au

Ne

w Z

e

Sou

th


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Datastream. Data since 1984 or earliest available.

15

Current 60/40 Drawdowns – A Long Time Between Drinks!gToday’s Real Value of a 60/40 Portfolio, vs. when Current Water Mark Was First Recorded

United States (first recorded in March 2000)

Germany and Spain (February 2000)Germany and Spain (February 2000)

Hungary (December 1999)

F (N b 1999)France (November 1999)

Netherlands (April 1999)

Finland (December 1998)

Belgium (February 1998)

Italy (December 1997)

Portugal (April 1997)Portugal (April 1997)

Ireland (March 1993)


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Japan (March 1987)Source: Deutsche Bank, Datastream.

16

The Curse of Correlation Instabilityy… Stock and Bond Correlations are Highly Regime Dependent

St k B d R t C l ti

Stock and Bond Return Correlation in the US (left) and Globally (right)

20%

30%

0.50

0.75

1.00Stock - Bond Return Correlation (lhs, 3yr rolling window)CPI (rhs, yr/yr)

0 50

0.75

1.00

Stock-Bond Return CorrelationsHigh Average Low

0%

10%

0.00

0.25

0.50

-0.25

0.00

0.25

0.50

-20%

-10%

-0.50

-0.25

-1.00

-0.75

-0.50

S n y K e y a n d ds

m a d n ay rk d a d al

ce p.

ry d a o

*Based on montly return correlations over a rolling 3year window, since 1984 or earliest available

-30%-1.00

-0.75

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011U

Jap

aG

erm

an UF

ran

cIt

alC

an

ad

Sp

aiSw

itze

rlan

Ne

the

rla

nd

Be

lgiu

mA

ust

riIr

ela

nSw

ed

eN

orw

aD

en

mar

Fin

lan

Au

stra

liN

ew

Ze

ala

nP

ort

ug a

Gre

ec

Cze

ch R

ep

Hu

ng

ar

Po

lan

So

uth

Afr

icM

exi

c


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Robert Shiller database, Datastream. Non-US data since 1984 or earliest available.

17

60/40 Portfolios are Woefully Unbalancedy… Dollar Weights Do Not Represent Risk Contributions

Stock and Bond Contribution to Total Portfolio Variability

Stock and Bond Return Correlation to Total Portfolio

100%

Contribution to Portfolio VariabilityBond Contribution Stock Contribution

0.8

1.0Stocks Bonds

40%

60%

80%

0 2

0.4

0.6

0%

20%

d y y s a d m p. n n d d d al k e n S y a a K a e o y

-0.2

0.0

0.2

d . d y a s n d y d m n n y e y k l d o a K a a e S

Fin

lan

dG

erm

anN

orw

ayN

eth

erl

and

Au

stri

Swit

zerl

and

Be

lgiu

mC

zech

Re

pJa

pan

Swe

de

Ne

w Z

eal

and

Po

lan

dIr

ela

nd

Po

rtu

gaD

en

mar

Fran

cSp

ai US

Ital

yC

anad

Sou

th A

fric U

Au

stra

liG

ree

cM

exi

coH

un

gar

Fin

lan

dC

zech

Re

p.

Po

lan

dG

erm

any

Au

stri

aN

eth

erl

and

sSp

ain

Ne

w Z

eal

and

No

rway

Swit

zerl

and

Be

lgiu

mSw

ed

en

Jap

anIt

aly

Fran

ceH

un

gary

De

nm

ark

Po

rtu

gaIr

ela

nd

Me

xico

Au

stra

lia UK

Can

ada

Sou

th A

fric

aG

ree

ce US


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Datastream. Data since 1984 or earliest available.

18

Forward-Looking 60/40 Valuation Forecasts - Worrisome g… Only Sustained Deflation Risk Can Keep Bond Yields Low

Starting Valuation Levels Forecast Bond Returns Reasonably Well

The Last Occasion 10y USTs traded at 2%, a 45-year Bear Market Followed

800

Real Total Bond Return Index Peak-to-Trough Drawdown

B d l 56% i l

16%

18%10y UST Yields, Advanced 10yrs

Subsequent Realized 10yr Compound Annual Nominal Returns

200

400

Bonds lost 56% in real termsfrom 1941 to 1986!

10%

12%

14%

16%

50

100

4%

6%

8%Corr = 0.96

25

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

0%

2%

1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011 2021


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


19

Forward-Looking 60/40 Valuation Forecasts - Worrisome g… In FI space, only Australian/EM Real Yields Look Interesting

Bond/Bill Share of Pension Fund Assets

High Real Yields Compensate for Illiquidity Risk in Aust/EM

78

Inflation-Linked Govt Bond Yields (%)

5y 10y 20-30y

70%

80%

90%

q y

23456

30%

40%

50%

60%

-2-101

S K e y y n n a a l o l a a d y e a

0%

10%

20%

30%

p. o y l . k a d n y s d e a al e y m y n a d y S a a a

US

UK

Fran

ce

Ger

man

y

Italy

Japa

n

Swed

en

Cana

da

Aus

tral

ia

Braz

i

Mex

ico

Isra

e

Sout

h A

fric

a

Sout

h Ko

rea

Thai

land

Turk

ey

Chile

Colo

mbi

a

Cze

ch R

ep

Me

xico

Hu

nga

ryIs

rae

Slo

vak

Re

pD

en

mar

kSl

ove

nia

Po

lan

dSp

ain

No

rway

Ne

the

rlan

ds

Ice

lan

dG

ree

ceA

ust

ria

Po

rtu

gaC

hile

Ital

yB

elg

ium

Ge

rman

yJa

pan

Can

ada

Fin

lan

dTu

rke

yU

SK

ore

aEs

ton

iaA

ust

ralia


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank , OECD, Bloomberg Finance LP

Forward-Looking 60/40 Valuation Forecasts - Worrisome g… Corporate Earnings are Already Way Above Trend, and the Low Labor Share of GDP is Fuelling Unrest Around the World

13%

15% US Corporate Profits, as % Share of GDP

+1Std Dev = 11 1% -1.0

-0.5

0.0Real S&P Earnings (Log Scale)

9%

11%

Ave = 9.1%

+1 Std Dev = 11.1%

-2.5

-2.0

-1.5

1.0

5%

7%-1 Std Dev = 7.1%

R² = 0.65

-4.0

-3.5

-3.0

3%

1947 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 2012

-4.5

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bureau of Economic Analysis, Robert Shiller database

21

Forward-Looking 60/40 Valuation Forecasts - Worrisome g… Stocks Aren’t Cheap on Replacement Cost or CAPE

2.0 Tobin's Q for US Equities50 Cyclically-Adjusted P/E Multiple for S&P500

1 2

1.4

1.6

1.8

35

40

45

50 Cyclically Adjusted P/E Multiple for S&P500

0 6

0.8

1.0

1.2

Ave = 0.73

+1 Std Dev = 1.04

15

20

25

30

Ave = 18.4x

+1 Std Dev = 26.1x

0.0

0.2

0.4

0.6

-1 Std Dev = 0.41

0

5

10

15

-1 Std Dev = 10.7x

1946 1951 1956 1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011 1909 1919 1929 1939 1949 1959 1969 1979 1989 1999 2009


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Federal Reserve, Robert Shiller database

22

Forward-Looking 60/40 Valuation Forecasts - Worrisome g… We Estimate Real 10yr Stock Returns @ 2.1% and Real 10yr Bond Returns @ -0.3% … 60/40 to deliver just 1.1% p.a.?

Probability-Weighted Scenario Analysis for 10yr Real US Stock Returns

Scenario Dividend Yield Real EPS Growth Cyclically-Adjusted PE Multiple E{Return} Probability E{R} * Prob

#1: Constant (@2.1%) Constant (growth @2.9% p.a.) Contracts (@2% p.a. from 22x to 18x) 3.0% 25% 0.75%

#2: Constant (@2.1%) Decelerates (growth @1% p.a.) Constant (22x) 3.1% 25% 0.78%

#3: Constant (@2.1%) Decelerates (growth @1% p.a.) Contracts (@2% p.a. from 22x to 18x) 1.1% 50% 0.55%

Sum 100% 2.1%


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


23

One Eye on the Past, Another on the Futurey ,Salient Features of the 1970s Macro Environment

High unemployment, yet sticky inflation (a high Misery Index)

Widespread social unrest and political turmoilWidespread social unrest and political turmoil

Elevated and volatile energy and commodity prices

Elevated currency volatility and concern over reserve currency debasement

Elevated inflation volatility y

Low real yields on government bonds

Rising government regulation and involvement in the economy

Decelerating productivity growth

Heightened geopolitical instability


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

24

Stocks and Bonds Cannot Handle Stagflationg60/40 is Ill-equipped for a 1970s-like Macro Environment

2.7%

Real Equity Returns Real Bond Returns Real 60/40 Portfolio Returns

1.0%

-0.3% -0 4% 3%

0%

3%

3%

0%

3%

0.4%

-2.6% -2.6% -3.2%

9%

-6%

-3%

9%

-6%

-3%

-11.1% -11.4%-15%

-12%

-9%

-15%

-12%

-9%

-15%-15%

Cana

da

Japa

n US

erm

any

UK

Fran

ce

Italy

Spain

G8-A

ve

G


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


25

Key Takeaways for the 60/40 Policy Portfolioy y y

It ignores strong evidence of regime dependence, regime persistence, and time-i ti i l t t t ( d i diti l i l di )variation in long-term asset returns (rendering unconditional averages misleading)

It assumes rebalancing is the best form of risk management, ignoring a role for hedging strategies or bubble identification as alternative risk mitigation approacheshedging strategies or bubble identification as alternative risk mitigation approaches

It assumes stable stock/bond correlations and stable diversification benefits – it ignores the fact that stocks and bonds are positively correlated in 2 out of 3 macroignores the fact that stocks and bonds are positively correlated in 2 out of 3 macro states (bonds consume significant allocations without offering reliable equity hedges)

Risk weights are not the same as dollar weights - equities account for around 95% g g qof portfolio variability in a 60/40 mix of stocks and bonds

Lengthy and severe 60/40 portfolio drawdowns are commonplace

The 60/40 portfolio was grossly ill-equipped to handle the stagflationary macro environment of the 1970s, a period bearing many similarities to today

Forward-looking return projections suggest a 1% real return p.a. for the 60/40 portfolio over the next decade in the US


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

p p

26

Part IIPart II.

From Second Generation Asset AllocationFrom Second Generation Asset Allocation

(“More Asset Classes Means I’m Diversified”)( More Asset Classes Means I m Diversified )

to… to …

Third Generation Asset AllocationThird Generation Asset Allocation

(“Diversification by Risk Factors”)( Diversification by Risk Factors )


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

27

Classic Portfolio Theoryy… If It’s Broken, Fix It – or Throw Out Your MV Optimizer !

Classic Portfolio Theory Reality

I t ti lBehavioral biases overwhelm analytical decision making (the pre-frontel cortex is especially

Investors are rationaly g ( p p y

overwhelmed when uncertainty is high); Psychologists have found > 100 biases

Investors maximize utility Investors engage in 'satisficing' ( we take shortcuts - near enough is good enough)

I t h if i k t l Ri k t l diff bj ti d b i i lth l lInvestors have uniform risk tolerances Risk tolerances differ across objectives, age, and beginning wealth levels

Investors view losses mathematically and smoothly Financial losses are processed in the same area of the brain as mortal danger!

Investors care largely about end of period wealth Intra horizon path dependency dramatically impacts investor behaviorInvestors care largely about end-of-period wealth Intra-horizon path dependency dramatically impacts investor behavior

Returns are normally distributed Almost all asset classes and securities exhibit signficiant skew and fat tails

Standard deviation defines the risk of a portfolioRisk can include liquidity, solvency, vulnerability to extreme or permanent loss;

Standard deviation defines the risk of a portfolioVolatility in the left tail is perceived differently from volatility in the right tail

Expected returns, volatility and correlations are static Return distribution parameters are dramatically time-varying and regime-dependent

Markets are largely efficient Dramatically time-varying risk premia can be rational or reflect inefficiencies; Bubbles exist!Markets are largely efficient Dramatically time varying risk premia can be rational or reflect inefficiencies; Bubbles exist!


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank

28

Most Alternative Assets Are Short a Common Risk FactorA Portfolio of Leverage-Sensitive Alternatives is Not a Hedge

50.6%

60%Alternative Asset Class Performance (2008-09)

2008 2009

20.0% 19.0%28.0% 30.0%

13.5%

50.6%

20%

40%

2008 2009

0%

20%

-19.0%

-36.2% -37.7% -40.7%-40%

-20%

0 %-46.5%

-60.0%

-80%

-60%

Source: Deutsche Bank, Bloomberg Finance LP. All returns are $USD-based total returns. Hedge Fund returns represented by the Hedge Fund Research Index Fund Weighted C it I d I f t t t t d b th UBS Gl b l I f t t E it I d REIT t d b th FTSE NAREIT E it I d W ld E it t

Hedge Funds Infrastructure REITs World Equities Commodities Private Equity


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Composite Index. Infrastructure returns represented by the UBS Global Infrastructure Equity Index. REITs represented by the FTSE NAREIT Equity Index. World Equity returns based on MSCI World Index. Commodity returns based on the GS Commodity Index. Private Equity returns depicted by the Red Rocks global listed private equity index

29

Hedge Fund Returns – Increasingly Equity Beta-Driveng g y q y… A Questionable Business Case for Many Hedge Fund Styles

C l i f HF R S&P500 (lh ) H d F d Al h S&P500 ( h ) 1 0

Correlation of Hedge Fund Returns vs. S&P500 - On the Rise

15%

18%

0 80

0.85

0.90Correlation of HF Returns vs. S&P500 (lhs) Hedge Fund Alpha vs. S&P500 (rhs)

0.6

0.8

1.0Since August 2007 Dec 1997 - July 2007

9%

12%

0.70

0.75

0.80

0 0

0.2

0.4

3%

6%

0.55

0.60

0.65

Alpha and correlations based on

-0.2

0.0

Equi

ty

ectio

nal

eigh

ted)

ng M

kts

t Dri

ven

ex-J

apan

M E

MEA

rger

Arb

M L

atA

m

mpo

site

stre

ssed

ve V

alue

e Cr

edit

vert

Arb

ulti-

Stra

t

rvat

ive)

Neu

tral

te Is

sues

Back

ed

Mac

ro

c M

acro

0%

3%

0.45

0.50

94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

Alpha and correlations based on monthly returns over four-year rolling window

Equi

ty Q

uant

Dir

e

ompo

site

(Fun

d-W

e

Emer

gi

Even

t

EM A

sia

e EM

Mer EM

Fund

of F

unds

Com Dis

Rela

tiv

FI C

orpo

rate

FI C

onv

Mu

nd o

f Fun

ds (

Cons

e

Equi

ty M

kt

Priv

a t

FI A

sset

Syst

emat

i c

Co Fun


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, HFRI.

30

Most Alternative Assets Are Short a Common Risk Factor14 of 18 HF Strategies Simultaneously Suffered Their Worst Drawdown - ‘Convergence’ Strategies Need Benign Liquidity Conditions

HF Strategy Largest Drawdown Date of Peak Drawdown

Equity Short Bias -52.0% Feb-00Equity Short Bias 52.0% Feb 00

Emerging Markets -43.4% Sep-98

Convertible Arbitrage -35.3% Nov-08

Equity Hedge -30.6% Feb-09

Equity Quant -31.1% Feb-09

Fixed Income -28.2% Dec-08

Distressed -27.4% Mar-09

Event Driven -24.8% Feb-09Event Driven 24.8% Feb 09

Fund of Funds Composite -22.2% Dec-08

Fund of Funds Diversified -21.8% Dec-08

Multi-Strategy -21.5% Dec-08

HF Weighted Composite -21.4% Feb-09

Fund of Funds Conservative -20.4% Dec-08

Relative Value -18.0% Dec-08Macro -10.7% Apr-94p

Equity Mkt Neutral -9.2% Apr-09

Merger Arbitrage -8.1% Nov-08Systematic Macro -5.9% Jun-11


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, HFRI. Data sample 1997-2011.

31

Most Alternative Assets Are Short a Common Risk Factor… HF and Equity Correlations Are Higher in Stressful Times

1.0

Correlation of Monthly Hedge Fund & MSCI World Equity Returns

(Conditional on Stock Returns That Month)

0 2

0.4

0.6

0.8( )

-0.4

-0.2

0.0

0.2

MSCI World falls by more than 1 Std Dev Other times

-0.8

-0.6

0.4

trat

edit

alue

uity ven

ted) Arb

site

ive)

Mkt

s

tAm sed

MEA Ar

b

pan

onal

ked

tral

ues

acro

Bias

acro

Mul

ti-St

I Cor

pora

te C

re

Relat

ive V

a Eq

Even

t Dri v

(Fun

d-W

eigh

t

FI Co

nver

t A

Fund

s Com

pos

nds (

Cons

erva

t

Emer

ging M

EM La

t

Distr

es

EM E M

Mer

ger

EM A

sia e

x-Ja

p

Quan

t Dire

ctio

FI As

set B

ac

Equi

ty M

kt N

eu

Priva

te Is

s Ma

Equi

ty Sh

ort B

Syste

mat

ic M

a

F

Com

posit

e

Fund

of

Fund

of Fu

n

Equi

ty E


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, HFRI. Data based on monthly returns from 1997-2011.

32

Equities and Hedge Funds Load onto Similar Factorsq g… Equal Capital Contributions, Unequal Risk Contributions

A Portfolio with 1/3 of Capital Spread AcrossBonds, Stocks and HFs is Not Diversified !

70%

80%

Asset Class Dollar Weights (Equal) Asset Class Contribution to Portfolio Variability

50%

60%

70%98% !

30%

40%

10%

20%

0%

USTs (7-10y) S&P500 Hedge Funds (HFRI FoF)


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, HFRI. Data sample 1997-2011.

33

Three 3-Dimensions of Risk Factor/Premia ExposurepBeta Risk Premia, Style Risk Premia and Systemic Risk Premia

Beta Risk Premia

B d D ti- Bond Duration - Credit Risk Premia- Equity Risk Premia- Commodity Risk Premia- Alternatives

Style Risk Premia Systemic/Macro Risk- Value Premium- Carry Premium- Momentum Premium

- Growth Risk- Inflation Volatility Risk- Liquidity Risk

- Volatility Premium- Illiquidity Premium- Size Premium

q y- Sovereign Risk


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank.

Size Premium

34

Building Portfolios of Risk Factors (… not Assets per-se)g ( p )An Example - Should I add High Yield to my Portfolio?

Risk Factor ExposureRisk Factor ExposureBeta Risk Premia Bond Duration +

Credit Risk + Credit Risk + Equity Risk + Commodity Risk

Style Risk Premia Value + Momentum Carry + Illiquidity +

Volatility - Volatility Size

Systemic Risk Premia Liquidity - Growth + Inflation Volatility -


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Sovereign -Source: Deutsche Bank

35

Risk Factors Explain Stock/Bond Correlation Instabilityp yStocks and Bonds Diversify One Another Only in One State

Stocks Bonds

Increase in E{Growth} + -Increase in E{Growth} + -

Increase in E{Inflation} - -

Increase in E{Sovereign Risk} - -Increase in E{Sovereign Risk}


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank

36

Risk Factors Explain Stock/Bond Correlation Instabilityp yBoth Stocks and Bonds are Short Inflation and Sovereign Risk

Stock and Bond Correlations (US left, Europe right) - Only Negative when Inflation and Sovereign Risk is Contained

0.8

1.0Correlation of Equity & 10yr Bond Returns

Ireland Spain Portugal Italy Greece

20%

30%

0.75

1.00Stock - Bond Return Correlation (lhs, 3yr rolling window)CPI (rhs, yr/yr)

0 0

0.2

0.4

0.6

0%

10%

0.00

0.25

0.50

-0.6

-0.4

-0.2

0.0

20%

-10%

-0.50

-0.25

-1.0

-0.8

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11-30%

-20%

-1.00

-0.75

1901 1911 1921 1931 1941 1951 1961 1971 1981 1991 2001 2011


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Robert Shiller, Bloomberg Finance LP.

37

Style Risk Premia is Uncorrelated …y… Within and Across Asset Classes

FX Rates Comm World Equity Indices

US Stocks

Japan Stocks

AxJ Stocks


US Stocks

Japan Stocks

AxJ Stocks


US Stocks

Japan Stocks

AxJ Stocks

VALUE CARRY MOMENTUM

FX 1.00 -0.48 -0.02 -0.02 0.00 0.01 0.17 -0.51 -0.11 -0.05 0.21 0.00 -0.01 0.19 -0.26 -0.17 -0.02 -0.17 -0.04 0.02 -0.01Rates 1.00 -0.01 0.11 0.19 -0.05 -0.05 0.49 -0.01 0.08 -0.20 0.06 0.05 -0.05 0.03 0.04 0.02 0.06 -0.17 -0.07 0.06

Commods 1.00 0.03 -0.06 -0.07 0.05 0.06 -0.04 -0.11 0.06 -0.03 -0.03 -0.01 0.00 -0.04 0.50 0.14 0.10 0.07 -0.09World Equity Indices 1.00 0.22 0.22 0.21 0.14 0.04 0.03 0.41 0.14 0.13 0.18 -0.08 -0.16 -0.01 -0.38 -0.13 -0.05 -0.05VALUE World Equity Indices 1.00 0.22 0.22 0.21 0.14 0.04 0.03 0.41 0.14 0.13 0.18 0.08 0.16 0.01 0.38 0.13 0.05 0.05

US Stocks 1.00 0.28 0.22 0.13 -0.02 0.10 0.14 0.47 0.18 0.09 -0.16 -0.16 -0.12 -0.24 -0.67 -0.28 -0.12Japan Stocks 1.00 0.21 -0.03 0.15 0.06 0.25 0.05 0.78 0.24 -0.14 -0.19 -0.01 -0.25 -0.21 -0.54 -0.21

AxJ Stocks 1.00 -0.10 0.00 -0.02 0.25 0.12 0.19 0.48 -0.14 -0.08 -0.07 -0.24 -0.23 -0.27 -0.29FX 1.00 0.03 0.10 -0.17 0.02 -0.06 -0.12 0.17 -0.01 0.06 0.05 -0.29 -0.12 0.01

VALUE

Rates 1.00 0.04 0.08 -0.13 0.08 0.08 0.12 0.08 0.07 -0.07 0.09 0.00 0.04Commods 1.00 -0.05 0.06 0.02 -0.10 0.00 0.00 -0.09 -0.07 -0.17 -0.10 -0.08

World Equity Indices 1.00 0.11 0.27 0.47 -0.16 -0.14 -0.03 -0.54 -0.10 -0.13 -0.23US Stocks 1.00 0.08 0.02 -0.06 0.02 -0.17 -0.11 -0.40 -0.11 -0.12

Japan Stocks 1.00 0.27 -0.22 -0.14 0.01 -0.24 -0.14 -0.66 -0.31

CARRY

p

AxJ Stocks 1.00 -0.09 0.01 -0.01 -0.31 -0.14 -0.24 -0.27FX 1.00 0.59 0.03 0.19 0.18 0.22 0.19

Rates 1.00 0.05 0.22 0.21 0.12 0.04Commods 1.00 0.19 0.11 0.04 0.01

W ld E i I di 1 00 0 33 0 27 0 31

S D t h B k D t t Bl b Fi LP L /Sh t thl tf li t i $US t f 1995 2011 S “Th R l f Ri k F t Di ifi ti ”

World Equity Indices 1.00 0.33 0.27 0.31US Stocks 1.00 0.40 0.25

Japan Stocks 1.00 0.37AxJ Stocks 1.00

MOMENTUM


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Datastream, Bloomberg Finance LP. Long/Short monthly portfolio returns in $US-terms from 1995-2011. See, “The Role of Risk Factor Diversification”, October 2011, Brad Jones.

38

Style Risk Premia is Uncorrelated …y… Within and Across Asset Classes

50%Global Value Portfolio Global Carry Portfolio Global Momentum Portfolio

40%

20%

30%

0%

10%

-10%

0%

-20%

96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

S D t h B k D t t Bl b Fi LP L /Sh t thl tf li t i $US t f 1995 2011 Th V l C d M t P tf li


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Datastream, Bloomberg Finance LP. Long/Short monthly portfolio returns in $US-terms from 1995-2011. The Value, Carry and Momentum Portfolios are volatility-weighted portfolios of long/short strategies across seven asset classes. See, “The Role of Risk Factor Diversification”, October 2011, Brad Jones.

39

A Portfolio of Style Risk Premia vs. Beta Risk Premiay… Different Return Sources, Low Portfolio Drawdowns

800Global Risk Premia Portfolio vs. Equity, Bond & HF BetaMSCI World Equities (CAGR=4.6%, St Dev=16.2%)

400

MSCI World Equities (CAGR 4.6%, St Dev 16.2%)

Citi World Govt Bonds (CAGR=5.6%, St Dev=7.6%)

Hedge Fund Research Composite (CAGR=8.6%, St Dev=7.4%)

Gl b l Ri k P i P tf li (CAGR 11 9% St D 4 0%)

200

Global Risk Premia Portfolio (CAGR=11.9%, St Dev=4.0%)

100

200

100

Total Return Indices Indexed to 100 at November 199550

95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11

S D t h B k D t t Bl b Fi LP L /Sh t thl tf li t i $US t f 1995 2011 Th Gl b l Ri k P i i l tilit i ht d


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Datastream, Bloomberg Finance LP. Long/Short monthly portfolio returns in $US-terms from 1995-2011. The Global Risk Premia is a volatility-weighted portfolio of 21 long/short strategies (value, carry and momentum, across seven asset classes). See, “The Role of Risk Factor Diversification”, October 2011, Brad Jones.

40

Two Tweaks in Harvesting Style Risk Premia g yIs Constant Exposure to Risk Premia the Best We Can Do?

Like traditional stock or bond risk premia, the ex-ante opportunity set across alternative risk premia’s is highly time-varying – if this time-variation is not completely random, we may have a shot at improving on a constant/passive exposure to alternative risk premia

1. Exploit Factor Momentum – condition factor exposure on a rolling performance window:Assumes asset returns are regime dependent and time-varyingg p y gAssumes there is persistence in regimes – long waves of factor outperformance are subsequently followed by long waves of ‘factor decay’ (the biology of capitalism) Assumes turning points/regime shifts in returns to factors cannot be reliably predictedAssumes turning points/regime shifts in returns to factors cannot be reliably predicted (ie. who knows when dividend yield will work again - but when/if it does, we will use it)

2 Take Factor Tilts - on the basis of conditional information which identifies the richness of2. Take Factor Tilts on the basis of conditional information which identifies the richness of the opportunity set, ex-ante:

Also assumes asset returns are regime dependent and time-varyingBut assumes we can reliably measure the ex-ante opportunity set (ie. future value outperformance is conditional on high current valuation dispersion across stocks)Assumes we have some ability in timing turning points in factor returns (be careful –


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

y g g p (this is easier done for some factors than others!)

41

Factor Tilts – Some ExamplespCan Factor Exposure be “Conditioned” (without forecasting)?

The returns to value investing in equity markets tend to be higher than usual when:Initial valuation dispersion between cheap and expensive stocks is unusually largeThis dispersion cannot be explained away by long-term earnings projectionsThis dispersion cannot be explained away by long term earnings projectionsLiquidity risk is low (this helps to neutralize the bankruptcy/financial distress risk sometimes associated with cheap stocks, but can change quickly)N h i i i l di i ll h ld i 2000 f hi h l i ifi lNote these initial conditions all held in 2000 – after which value significantly outperformed (around the world) for seven straight years

The returns to carry trades in the currency market tend to be abnormally high when:Currencies comprising the high (low) yielders are fundamentally cheap (expensive)There is large dispersion in interest rate differentials across countriesThere is large dispersion in interest rate differentials across countriesHigh real rates in the higher yielding basket of currencies reflect strong domestic economic growth conditions (ie. monetary policy), and are not risk premiums reflecting elevated current account deficits inflation or general sovereign riskreflecting elevated current account deficits, inflation or general sovereign riskBroad global liquidity conditions are benign (incentivizing investors to write “financial catastrophe insurance” by participating in strategies with a high probability of steady

t b t l b bilit f di t )Brad Jones; [email protected]; +852 2203 8170 January 2012

Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

returns, but a low probability of disaster)

42

Adapting to Regime Shifts (Part I) - Covariance Regimesp g g ( ) gWorld Equity Returns are Drawn from Two Distributions –The Case for a Tactical Approach to Managing Covariance Regimes

Regime: Turbulence Tranquility

400Compound Annual Growth Rate -1.5% 5.5%

Geometric (Annualized Daily) Return -3.1% 10.6%

Standard Deviation 19.0% 10.9%

Reward/Risk Ratio -0.16 0.97

Downside Standard Deviation 12 8% 6 7% 200

400

Turbulence Tranquility

Downside Standard Deviation 12.8% 6.7%

Average Downside Return -0.4% -0.2%

Daily Return Skew -0.61 -0.16

Daily Return Kurtosis 5.7 3.5

% Up Days 54.5% 56.2%100

200

Maximum Drawdown -55.2% -21.8%

Calmar Ratio -0.03 0.25

Worst Day -8.1% -4.4%

Ratio of Worst Day to Best Day 1.1 0.8

95%Downside VaR -2 0% -1 1% 50

100

95% Downside VaR 2.0% 1.1%

95% Downside C-VaR -3.1% -2.4%

Average Length of Turbulent Regime (days) 37

Longest Turbulent Period (days) 219

50

Jan

-95

Jan

-96

Jan

-97

Jan

-98

Jan

-99

Jan

-00

Jan

-01

Jan

-02

Jan

-03

Jan

-04

Jan

-05

Jan

-06

Jan

-07

Jan

-08

Jan

-09

Jan

-10

Jan

-11

Jan

-12

S D t h B k Bl b Fi LP MSCI D il $US b d t d t i 1995 42 t i ll i ht d “T b l ” d fi d i d h

Signal Switches Per Year 2.2


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, MSCI. Daily $US-based return data since 1995, across 42 countries, equally-weighted. “Turbulence” defined as periods where the covariance of daily country equity index returns is above the average of the past 252 trading days.

43

Adapting to Regime Shifts (Part II) – Factor Regimesp g g ( ) gLong/Short World Equity Index Returns, Conditional on Whether a Factor Has Been Profitable in the Past Six Months …

Long/Short World Equity Index Returns, Conditional on Past Factor Performance

Long/Short World Equity Index Hit Rate, Conditional on Past Factor Performance

When Factor Has Generated Positive Alpha in Prior 6mthsWhen Factor Has NOT Generated Positive Alpha in Prior 6mths

When Factor Has Generated Positive Alpha in Prior 6mthsWhen Factor Has Not Generated Positive Alpha in Prior 6mths

Conditional on Past Factor Performance Conditional on Past Factor Performance

50%

55%

When Factor Has NOT Generated Positive Alpha in Prior 6mths

4%

5%

When Factor Has Not Generated Positive Alpha in Prior 6mths

40%

45%

2%

3%

30%

35%

Median Subsequent Hit Rate Average Subsequent Hit Rate

0%

1%

Median Subsequent Return Average Subsequent Return Across 51 Factors Across 51 FactorsAcross 51 Factors Across 51 Factors


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, MSCI. Daily $US-based return data since 1995, across 42 countries, equally-weighted.

44

Adapting to Regime Shifts (Part III) – Momentum Regimesp g g ( ) gPlay Defence First – Just Stay Clear of Big Bear Markets, and the Long-term Equity Risk Premium Will Look After You!

World Equity Index Returns: Buy and Hold vs Long or Flat

Distribution of Annual World Equity Index ReturnsBuy-and-Hold vs. Long-or-Flat

Model Buy & Hold Model Buy & Hold

Since 1970 Since 1999 30%Momentum Model Buy and Hold

World Equity Index Returns

Model Buy & Hold Model Buy & HoldCAGR 9.3% 7.7% 7.2% 2.4%St Dev 8.5% 14.4% 9.9% 18.1%Return per unit of Std Dev 1.10 0.53 0.72 0.13Downside Volatility 7 6% 13 0% 7 9% 16 0%

20%

25%

Momentum Model Buy and Hold

Downside Volatility 7.6% 13.0% 7.9% 16.0%Return per unit of Downside Std Dev 1.23 0.59 0.90 0.15Max Drawdown -23% -58% -21% -58%Length of Max DD (yrs) 5.5 7.0 3.8 4.9Calmar Ratio (DD/CAGR) 0 40 0 13 0 33 0 04

10%

15%

Calmar Ratio (DD/CAGR) 0.40 0.13 0.33 0.04% Up Weeks 59% 59% 55% 56%Average Down Week -0.8% -1.5% -0.9% -1.9%Worst Week -17% -23% -8% -23%Best Year 59% 68% 29% 45%

0%

5%

-40% -30% -20% -10% 0% to 0% 10% 20% 30% 40% 50%

S D t h B k Bl b Fi LP MSCI W kl $US b d t d t i 1970 42 t i ll i ht d Th M t M d l lt

Best Year 59% 68% 29% 45%Worst Year -9% -49% -9% -49%

to -50%

to -40%

to -30%

to -20%

-10% to 10%

to 20%

to 30%

to 40%

to 50%

to 60%


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, MSCI. Weekly $US-based return data since 1970, across 42 countries, equally-weighted. The Momentum Model results are based on a simple medium-term trend following strategy where the investor is either fully invested or out of the market completely (but not short).

45

Adapting to Regime Shifts (Part III) – Momentum Regimesp g g ( ) gMomentum Overlays Can Preserve Capital in Bear Markets, While Offering Participation in Bull Markets (ie. Synthetic Calls)

Only 20% of the Downside in Big Bear Markets

… and 75% of Participation in Big Bull MarketsBear Markets … Bull Markets

0%

1 2 3 4 52008 1973200219901974 68%70%

1 2 3 4 5Momentum Model Buy & Hold

-8%

-3%-2%

-5% -5%

%

-15%

-10%

-5%

0%59%

40% 39%

50% 49%45%

43%

40%

50%

60%

-19% -18% -17%

-35%

-30%

-25%

-20%29% 28%

20%

30%

40%

-49%

-37%

-50%

-45%

-40%Momentum Model Buy & Hold

0%

10%

1993 1999200919721989

S D t h B k Bl b Fi LP MSCI W kl $US b d t d t i 1970 42 t i ll i ht d Th M t M d l lt


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

Source: Deutsche Bank, Bloomberg Finance LP, MSCI. Weekly $US-based return data since 1970, across 42 countries, equally-weighted. The Momentum Model results are based on a simple medium-term trend following strategy where the investor is either fully invested or out of the market completely (but not short).

46

Adapting to Regime Shifts (Part III) – Momentum Regimes

Disciplined use of momentum overlays can defend against debilitating behavioral biases:

p g g ( ) gMomentum Overlays - Don’t Cede the Intellectual High Ground!

Disciplined use of momentum overlays can defend against debilitating behavioral biases:

Cognitive Dissonance - the tendency to disregard evidence contrary to one’s thesis;Overconfidence – most fund managers believe they have above-average skill; Prospect Theory/Loss Aversion - the tendency for investors to be risk-averse when

faced with the potential for gain (ie. take profits early), but turn risk-seeking when faced with the prospect for loss (ie. let losing trades run in the hope they come back). This

if t i ki k d tilit (fl tt f fit bl t d th l i t d )manifests in a kinked utility curve (flatter for profitable trades than losing trades).

Three explanations for why the momentum effect is still a wide-spread source of return, l ft it h b d t d b d ilong after it has been documented by academics:

Economic rationale – self-reinforcing positive feedback loops between the economy and financial assets (George Soros calls this ‘reflexivity’, while Hyman Minsky’sand financial assets (George Soros calls this reflexivity , while Hyman Minsky s‘Financial Instability Hypothesis’ stresses the role of leverage in amplifying the pro-cyclical nature of business cycles);

Institutional rationale – investors tend to minimize career risk by clinging tightly to y g g g ybenchmarks which are biased to over-weight securities with good recent performance;Behavioral rationale – investor risk reversion tends to be wealth dependent. Investors

also tend to initially under-react to new information (cognitive dissonance) as they


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

y ( g ) yextrapolate the recent past, before extrapolating the new trend once it begins to form

47

Concluding Remarks – Evolution Ahead in Asset Allocationg

The 60/40 Policy Portfolio, still the industry default setting, is far riskier than most think: It is subject to unacceptably large and lengthy drawdowns/shortfall riskIt is subject to unacceptably large and lengthy drawdowns/shortfall riskHas substantial embedded correlation risk (based on statistical/economic factors) Ignores regime dependence, and is ill-equipped for a ‘stag-lite’ macro environmentAt current valuation levels, offers virtually no prospect of realizing returns in line with the long-term average of 4% p.a. in real terms (more likely 1% p.a.)

The Second Generation Approach has been to expand into more assets (ie. alternatives):But most alternatives are short systemic liquidity risk, and so can compound losses of a equity-centric portfolio in a crisis (ie alternatives have a very high ‘stress beta’)of a equity centric portfolio in a crisis (ie. alternatives have a very high stress beta )New alternative sources of return will include genuinely orthogonal exposures like cat bonds, music/intellectual property rights, carbon/water credits, longevity swaps, etc.

The Third Generation Approach to portfolio construction will likely rest on three pillars: Risk factors and risk premias, rather than asset class silos, will be the building blocksRisk management should be a tactical and multi-dimensional process, incorporating the biological concepts of regime dependence, regime shifts and adaptationThe best features of the Endowment Model (centered on long-term risk premia) and


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

( g p )Macro Hedge Funds (focused on managing tail risk) will eventually be fused together

48

Appendix # 1.

Building an Investment Defense Against Behavioral Biases


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

49

Can A Process Triumph Over Behavioural Biases?pDefending Ourselves From … Ourselves

We roamed the African savannah for 130 000 years but have been trading stocksWe roamed the African savannah for 130,000 years, but have been trading stocks and bonds on organized exchanges for just 400 years* - our biological processes have not kept pace with developments in our career paths!This leaves us vulnerable to an array of behavioural biases that while optimal for survival in the jungle, are sub-optimal for decision making under uncertainty250 years ago Adam Smith characterized the behaviour of humans as one of250 years ago, Adam Smith characterized the behaviour of humans as one of conflict between ‘passions’ and ‘an impartial spectator’, but for much of the past century, the assumption of rational expectations has dominated in economics O l i th t 15 20 h t t d t f fi di f b h i lOnly in the past 15-20 years have we started to fuse findings from behavioural neuroscience and cognitive psychology into a new discipline that addresses suboptimal decision making – neuroeconomics, or behavioural financeWe cannot cure systematic biases – these are generally efficient and helpful for daily life (our brains engage in ‘heuristics’, ‘satisificing” and ‘boundedly rational’ decision making, preventing paralysis-by-analysis for trivial matters) …g, p g p y y y )… But we can develop processes to ameliorate the debilitating effects of behavioural biases in investment decision making in the face of uncertainty


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

* The Dutch East India Company was the first to issue stock and bonds to the general public in a limited liability structure via the Amsterdam Stock Exchange in 1602 (Exchange Handbook).

50

The Case for Process over DiscretionBehavioural Biases Help in Life, But not in the Markets

In response to the collapse of the South Sea Bubble Sir Isaac Newton declared heIn response to the collapse of the South Sea Bubble, Sir Isaac Newton declared he could calculate the motion of heavenly bodies, but not the madness of people When faced with heightened uncertainty, behavioural biases trump rational thoughtFinancial losses are processed in the same areas of the brain that respond to mortal danger - this only serves us well in running away from lions!Worse still in the face of large potential losses we exhibit risk seeking behavior butWorse still, in the face of large potential losses we exhibit risk-seeking behavior, but turn risk averse when faced with gains – we let losses run, but cut short winners!It is the release of chemical compounds that affect our decision making:

Oxytocin is associated with the herding effect (and feelings of trust/security)*Dopamine (affecting our pleasure/reward senses) is released when we anticipate the prospect of unusually large returns the neural activity of aanticipate the prospect of unusually large returns – the neural activity of a trader on a hot streak can be indistinguishable from someone on cocaine*

Deep value investing is so difficult in practise because isolation from herds leads to stimulation of the amygdala (fight/flight) which can overwhelm the analytical brain (prefrontal cortex) - bucking the consensus can activate the same areas of the brain that are triggered by physical pain* – it literally hurts to be a deep value investor!


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

* “Source: Your Money and Your Brain” (2007), Jason Zweig

51

The Case for Process over DiscretionMore than 100 Behavioural Biases Have Been Documented !

O fid bi th j it b li th i t thOverconfidence bias - the majority believe they are superior to the averageCognitive dissonance - the tendency to seek only evidence supporting one’s thesis Regret avoidance - a poor outcome in the past prevents objective appraisal inRegret avoidance a poor outcome in the past prevents objective appraisal in subsequent periods (“I will never buy tech stocks again”)Disposition effect/Asymmetric loss aversion - we take large risks in attempting to

id l b t i k (t k fit l ) i th f f t ti l iavoid any loss, but are risk averse (take profits early) in the face of potential gains Hindsight bias (Monday morning quarterbacking) - ex-post rationalization makes events seem more predictable than was the case in real time (“it was so obvious”)p ( )Self attribution bias - positive (negative) outcomes are due to us (exogenous events)Endowment affect – we value owned items higher than identical unowned itemsSadness effect - in order to bring about change, it increases the value placed on unowned items, and decreases that of owned items (antidepressants have been prescribed for compulsive shoppers and traders!)Familiarity bias - gives a false impression of control Anchoring effect - placing too much weight on just one piece of information (“I won’t swim in Australia as they have sharks in the water down there”)


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

swim in Australia as they have sharks in the water down there”)

52

Appendix # 2.

Noise vs. Signal

- The (Non-Linear) Role of Time


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

53

Noise vs. SignalgWhy Monitoring Your Portfolio Each Hour Won’t Help Performance

The return generating process is a function of signal (return) and noise (volatility)The signal/noise ratio varies dramatically through time - return (or drift) grows as a linear function of time, but standard deviation grows more slowly (at the root of time)Th i ifi t i li ti f thi ti d d t li l ti hiThere are significant implications from this time-dependent non-linear relationship:

at high frequencies, volatility swamps the drift (you only observe noise!)for instance in the case of an asset with 15% return and 15% volatility, thefor instance in the case of an asset with 15% return and 15% volatility, the signal/noise ratio is just 1% at 1-hourly frequency, but 29% at monthly frequencyput another way, the probability of this asset being higher over any given 1-hr period is j st 50 4% (a coin toss) b t 61 1% o er an gi en monthl periodperiod is just 50.4% (a coin toss), but 61.1% over any given monthly periodbecause we feel losses more intensely than gains of the same magnitude, high frequency trading will likely impose enormous emotional costs over timeat high frequencies, the ratio of transaction costs/returns is also very large (an asset appreciating 15% p.a. will rise just 0.06% on average each day, < bid/ask!)lowering the observation frequency increases signal/noise but at the potentiallowering the observation frequency increases signal/noise, but at the potential cost of missing big turning points (there is a trade-off or optimization problem)the largest gains in statistical efficiency (and hence emotional benefit) likely


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

occur when measuring volatility daily, but observing returns weekly or monthly54


Time is a natural filter for noiseTime is a natural filter for noise

Drift can ‘out-run’ volatility only as the length of holding period increases (volatility is a sprinter and will dominate over short periods, drift is a marathon runner)( y p p , )

Increasing the observation period (up to a point) can help save emotional calories!

70 7%

100.0%

80%

90%

100%Ratio of Signal to Noise

(For an asset with 15% return and 15% std dev)

90%95%

100%Probability Holding Period Produces a Positive Return

(For an asset with 15% return and 15% std dev)

50.0%

70.7%

40%

50%

60%

70%

69.1%

76.0%

84.1%

70%75%80%85%90%

0 2% 1.3%6.3%

13.9%

28.9%

10%

20%

30%

40%

50.1% 50.4%52.5%

55.5%

61.1%

55%60%65%70%

0.2% 1.3%0%

Min

ute

Ho

ur

Day

We

ek

Mo

nth

Qu

arte

r

Sem

i-A

nn

Year

50%M

inu

te

Ho

ur

Day

We

ek

Mo

nth

Qu

arte

r

Sem

i-A

nn

Year


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

S

Source: DB Global Markets Research, Bloomberg

55


The more volatile the asset, the longer time period typically required in order toThe more volatile the asset, the longer time period typically required in order to observe a reasonable amount of ‘signal’

Incremental benefits from extending the observation period seem to level out beyond g p ythe monthly frequency (and may be overtaken by other considerations)

1400%

1500%

Cumulative Increase in Signal/Noise Ratio (vs. 1 minute observation frequency)

1 4

1.6

Ratio of Pain to Pleasure Across Observation Periods* Assumes investor feels 1.5 units of pain for each unit of pleasure, and asset appreciates 15% p.a. with 15% std deviation

1100%

1200%

1300%

1400%

0.8

1.0

1.2

1.4

800%

900%

1000%

* For an asset with 15% return and 15% std deviation0.2

0.4

0.6

600%

700%

To Hourly To Daily To Weekly To Mthly To Qrtly To Semi Ann.

To Yearly

For an asset with 15% return and 15% std deviation0.0


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template


56

Noise vs. SignalgAs the Holding Period Increases, Noise Eventually Washes Out

20S&P500 Daily Returns Shown as # Std Deviations

(Frequency > 6 std deviations = 0 22%)20

S&P500 Weekly Returns Shown as # Std Deviations(Frequency > 6 std deviations = 0.07%)

12

14

16

18(Frequency > 6 std deviations = 0.22%)

12

14

16

18( q y )

4

6

8

10

4

6

8

10

0

2

27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11

0

2

27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11

14

16

18

20S&P500 Monthly Returns Shown as # Std Deviations

(Frequency > 6 std deviations = 0.1%)

14

16

18

20S&P500 Quarterly Returns Shown as # Std Deviations

(Frequency > 6 std deviations = 0%)

6

8

10

12

14

6

8

10

12

14

0

2

4

6

27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11

0

2

4

6

27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11 27 31 35 39 43 47 51 55 59 63 67 71 75 79 83 87 91 95 99 03 07 11


57

Appendix 1ppImportant DisclosuresAdditional Information Available upon Request

Analyst CertificationThe views expressed in this report accurately reflect the personal views of the undersigned lead analyst about the subject issuers and the securities of those issuers. In addition, the undersigned lead analyst has not and will not receive any compensation for providing a specific

d ti i i thi t B d Jrecommendation or view in this report. Brad Jones

For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at http://gm.db.com.


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

58

Buy: Based on a current 12-month view of total shareholder return (TSR = percentage change in share price from current price to

Equity Rating Key Equity Rating Dispersion and Banking Relationships

60 %450projected target price plus projected dividend yield), we recommend that investors buy the stock.

Sell: Based on a current 12-month view of total shareholder return, we recommend that investors sell the stock.

Hold: We take a neutral view on the stock 12 months out and based

60 %

35 %

150200250300350400450

Hold: We take a neutral view on the stock 12 months out and, based on this time horizon, do not recommend either a Buy or Sell.

Notes:

1. Newly issued research recommendations and target prices always supersede previously published research.

5 %12 % 11 % 6 %0

50100

Buy Hold Sell

2. Ratings definitions prior to 27 January, 2007 were:

Buy: Expected total return (including dividends) of 10% or moreover a 12-month period

Hold: Expected total return (including dividends) between -10%

Asia-Pacific Universe

Companies Covered Cos. w/ Banking Relationship

Hold: Expected total return (including dividends) between 10%and 10% over a 12-month period

Sell: Expected total return (including dividends) of -10% orworse over a 12-month period


Deutsche Bank

2010 DB Blue template

59

Regulatory Disclosures

1. Important Additional Conflict Disclosures

Aside from within this report, important conflict disclosures can also be found at https://gm.db.com/equities under the “Disclosures Lookup” and “Legal” tabs. Investors are strongly encouraged to review this information before investing.

2. Short-Term Trade Ideas

Deutsche Bank equity research analysts sometimes have shorter-term trade ideas (known as SOLAR ideas) that are consistent or inconsistent with Deutsche Bank’s existing longer term ratings. These trade ideas can be found at the SOLAR link at http://gm.db.com.

3. Country-Specific Disclosures

Australia & New Zealand: This research, and any access to it, is intended only for "wholesale clients" within the meaning of the Australian Corporations Act and , y , y g pNew Zealand Financial Advisors Act respectively.

Brazil: The views expressed above accurately reflect personal views of the authors about the subject company(ies) and its(their) securities, including in relation to Deutsche Bank. The compensation of the equity research analyst(s) is indirectly affected by revenues deriving from the business and financial transactions of Deutsche Bank.

EU countries: Disclosures relating to our obligations under MiFiD can be found at http://www.globalmarkets.db.com/riskdisclosures.EU countries: Disclosures relating to our obligations under MiFiD can be found at http://www.globalmarkets.db.com/riskdisclosures.

Japan: Disclosures under the Financial Instruments and Exchange Law: Company name – Deutsche Securities Inc. Registration number – Registered as a financial instruments dealer by the Head of the Kanto Local Finance Bureau (Kinsho) No. 117. Member of associations: JSDA, Type II Financial Instruments Firms Association, The Financial Futures Association of Japan, Japan Securities Investment Advisers Association. Commissions and risks involved in stock transactions – for stock transactions, we charge stock commissions and consumption tax by multiplying the transaction amount by the commission rate agreed with each customer. Stock transactions can lead to losses as a result of share price fluctuations and other factors. Transactions in foreign stocks can lead to additional losses stemming from foreign exchange fluctuations "Moody's" "Standard & Poor's" and "Fitch" mentioned in this report are not registered credit ratingadditional losses stemming from foreign exchange fluctuations. Moody s , Standard & Poor s , and Fitch mentioned in this report are not registered credit rating agencies in Japan unless “Japan” is specifically designated in the name of the entity.

Russia: This information, interpretation and opinions submitted herein are not in the context of, and do not constitute, any appraisal or evaluation activity requiring a license in the Russian Federation.


Deutsche Bank

11/01/2012 09:11:12 2010 DB Blue template

60

Global DisclaimerThe information and opinions in this report were prepared by Deutsche Bank AG or one of its affiliates (collectively "Deutsche Bank"). The information herein is believed to be reliable and has been obtained from public sources believed to be p p p p y ( y ) preliable. Deutsche Bank makes no representation as to the accuracy or completeness of such information.Deutsche Bank may engage in securities transactions, on a proprietary basis or otherwise, in a manner inconsistent with the view taken in this research report. In addition, others within Deutsche Bank, including strategists and sales staff, may take a view that is inconsistent with that taken in this research report.Opinions, estimates and projections in this report constitute the current judgement of the author as of the date of this report. They do not necessarily reflect the opinions of Deutsche Bank and are subject to change without notice. Deutsche Bank has no obligation to update, modify or amend this report or to otherwise notify a recipient thereof in the event that any opinion, forecast or estimate set forth herein, changes or subsequently becomes inaccurate. Prices and availability of financial instruments are subject to change without notice. This report is provided for informational purposes only. It is not an offer or a solicitation of an offer to buy or sell any financial instruments or to participate in any particular trading strategy. Target prices are inherently imprecise and a product of the analyst judgement.As a result of Deutsche Bank’s March 2010 acquisition of BHF-Bank AG, a security may be covered by more than one analyst within the Deutsche Bank group. Each of these analysts may use differing methodologies to value the security; as a

lt th d ti diff d th i t t d ti t f h id lresult, the recommendations may differ and the price targets and estimates of each may vary widely.In August 2009, Deutsche Bank instituted a new policy whereby analysts may choose not to set or maintain a target price of certain issuers under coverage with a Hold rating. In particular, this will typically occur for "Hold" rated stocks having a market cap smaller than most other companies in its sector or region. We believe that such policy will allow us to make best use of our resources. Please visit our website at http://gm.db.com to determine the target price of any stock. The financial instruments discussed in this report may not be suitable for all investors and investors must make their own informed investment decisions. Stock transactions can lead to losses as a result of price fluctuations and other factors. If a financial instrument is denominated in a currency other than an investor's currency, a change in exchange rates may adversely affect the investment. Past performance is not necessarily indicative of future results. Deutsche Bank may with respect to securities covered by this report, sell to or buy from customers on a principal basis, and consider this report in deciding to trade on a proprietary basis.Unless governing law provides otherwise, all transactions should be executed through the Deutsche Bank entity in the investor's home jurisdiction. In the U.S. this report is approved and/or distributed by Deutsche Bank Securities Inc., a member of the NYSE, the NASD, NFA and SIPC. In Germany this report is approved and/or communicated by Deutsche Bank AG Frankfurt authorized by the BaFin. In the United Kingdom this report is approved and/or communicated by Deutsche Bank AG London a member of the London Stock Exchange and regulated by the Financial Services Authority for the conduct of investment business in the UK and authorized by the BaFin This report is distributed in Hong Kong byDeutsche Bank AG London, a member of the London Stock Exchange and regulated by the Financial Services Authority for the conduct of investment business in the UK and authorized by the BaFin. This report is distributed in Hong Kong by Deutsche Bank AG, Hong Kong Branch, in Korea by Deutsche Securities Korea Co. This report is distributed in Singapore by Deutsche Bank AG, Singapore Branch, and recipients in Singapore of this report are to contact Deutsche Bank AG, Singapore Branch in respect of any matters arising from, or in connection with, this report. Where this report is issued or promulgated in Singapore to a person who is not an accredited investor, expert investor or institutional investor (as defined in the applicable Singapore laws and regulations), Deutsche Bank AG, Singapore Branch accepts legal responsibility to such person for the contents of this report. In Japan this report is approved and/or distributed by Deutsche Securities Inc. The information contained in this report does not constitute the provision of investment advice. In Australia, retail clients should obtain a copy of a Product Disclosure Statement (PDS) relating to any financial product referred to in this report and consider the PDS before making any decision about whether to acquire the product. Deutsche Bank AG Johannesburg is incorporated in the Federal Republic of Germany (Branch Register Number in South Africa: 1998/003298/10). Additional information relative to securities, other financial products or issuers discussed in this report is available upon request. This report may not be reproduced, distributed or published by any person for any purpose without Deutsche Bank's prior written consent. Please cite source when quoting.Copyright © 2012 Deutsche Bank AG


Deutsche Bank61

Rethinking Portfolio Construction andRi kM td Risk Management · Diversification based on...

Documents

Transcript of Rethinking Portfolio Construction andRi kM td Risk Management · Diversification based on...