Hedge Fund Market Neutral Strategies: Distinguishing Financial

and Operational Risk Factors

Stephen J. BrownNYU Stern

The Joint 14th Annual PBFEAand 2006 Annual FeAT Conference

 第十四屆亞太財務經濟及會計會議暨2006台灣財務工程學會聯合研討會

Distinguishing operational and financial risk

Historical perspectiveOperational risk

Characterized by conflicts of interest

Financial riskThe myth of market neutrality

Robust measure of tail risk neutrality

Conclusion

The History of Hedge Funds

The first hedge fund: Alfred Winslow Jones (1949)Limited Partnership (exempt from ’40 Act)Long-short strategy20% of profit, no fixed feeUsed short positions and leverage

“Hedge Fund” (Fortune magazine 1966) Tiger Fund (Institutional Investor 1986) George Soros $3.2Billion raid on the ERM

(1992) CalPERS (2000)

Institutional concern about risk

Fiduciary guidelines imply concern for riskFinancial riskOperational risk

Institutional demandGrowing popularity of market neutral

stylesExplosive growth of funds of fundsDemand for “market neutral” funds of

funds

Operational Risk

0

0.2

0.4

0.6

0.8

1

7 15 23 31 39 47 55 63 71 79 87

Duration (Months)

Frac

tion

of Fu

nds

Sur

viving

CTAs

HedgeFund

Source: Tremont TASS (Europe) Limited

Hedge fund failure is highly predictable …

Measuring operational risk

SEC registration requirement (Feb 2006)

2270 of TASS Funds that registeredHad better past performanceHad larger assets under management15.8% had prior legal/regulatory problems

What are the correlates of operational risk?

Correlates of operational risk

“Problem” Funds

“Non-Problem” Funds

N Mean

Median

N Mean

Median

Diff

Avg Return 356

0.89

0.80 1898

0.98 0.84 -0.09*

Std Dev 354

2.60

1.79 1897

2.74 2.08 -0.14

Sharpe Ratio 354

0.33

0.29 1897

0.39 0.30 -0.06*

AUM ($mm) 325

218.2

58.74 1647

180.2

54.00 38.00

Age (Years) 358

5.65

4.50 1912

4.99 3.92 0.66**

Management Fee (%)

358

1.37

1.25 1912

1.38 1.50 -0.01

Incentive Fee (%)

358

15.23

20.00 1912

17.52

20.00 -2.29**

High Water Mark

358

0.69

1.00 1912

0.82 1.00 -0.13**

Lockup Period (months)

358

4.07

0.00 1912

4.48 0.00 -0.41

External conflicts

Problem funds

Non problemfunds

With: N % Yes N % Yes

Broker/Dealer 359 73.8 1912 24.8

Investment Comp

359 50.4 1912 16.0

Investment Advisor

359 74.7 1912 41.3

Commodities Broker

359 53.5 1912 20.3

Bank 359 40.4 1912 9.8

Insurance 359 39.8 1912 9.4

Sponsor of LLP 359 56.8 1912 22.2

Internal conflicts

Problem funds Non problemfunds

With: N % Yes N % Yes

Trade securities with clients

359 30.1 1912 8.4

Allow trading on own account

359 85.2 1912 69.6

Recommend own securities 359 74.9 1912 50.8

In-house broker dealer 359 31.2 1912 2.3

Recommends own underwriting service

359 69.4 1912 46.8

Recommends commission fee items

359 22.6 1912 15.7

Recommends brokers 359 45.7 1912 38.4

Use broker provided external research

359 81.3 1912 69.9

Towards a univariate index of operational risk

TASS Variables SEC Variables

Previous Returns -0.27 In-house broker dealer 0.06

Previous Std. Dev. -0.36 Associated with broker dealer 0.24

Fund Age -0.10 Investment company association

0.25

Log of Assets 0.09 Investment advisor association

0.24

Reports Assets 0.07 Commodity trader association 0.44

Incentive Fee -0.89 Associated with bank or thrift 0.39

Margin -0.29 Associated with insurance co 0.42

Audited -0.21 Associated with ltd. partner syndicator

0.27

Personal Capital -0.26 Trade securities with clients 0.06

Onshore -0.11 Allow trading on own account -0.12

Open to Inv. 0.04 Recommend own securities 0.32

Accepts Managed Accts -0.13 Recommends own underwriting service

0.24

Recommends commission fee items

0.28

Recommends brokers -0.35

Use broker provided external research

-0.69

Correlation Between Fraction of owners who hold 75% of firm

0.17

TASS and ADV Panels 0.41 Fraction of domestic ownership

0.28

Financial Risk

0%10%20%30%40%50%60%70%80%90%

100%

0 10 20 30 40 50 60 70 80 90 100

Size of portfolio

Per

cent

of risk

Equities

S&P500 risk

Source: Elton and Gruber 1995. Risk is measured relative to the standard deviation of the average stock

Financial Risk

0%10%20%30%40%50%60%70%80%90%

100%

0 10 20 30 40 50 60 70 80 90 100

Size of portfolio

Per

cent

of risk Equities

Hedge Funds

S&P500 risk

Hedge Fund risk

Caught by the tail

“S&P500 returns at Treasury Bill risk”Most new funds claim to be “market

neutral”Zero correlation with benchmark

Zero correlation is not a strategyZero correlation is an outcome of a

strategy These strategies fail in liquidity crises

Risk is considerably understated New concept: “tail risk neutrality”

A market neutral strategy

Data

TASS hedge funds – both dead and alive

US funds with at least 10 returns, average of 40 max of 120.

Not a lot of data per fund, but plenty when the universe is combined – nearly 50,000 fund-month observations.

An example of ‘market neutrality’Fu

nd

Retu

rns

Market Returns0.2

0.2

0.4

0.6

0.8

0.6

0.8

0.4

1.5%

1.1%

0.8%

0.4%

Beta = .28, rho = .24

Assuming MVN returns

2.5%

1.9%

1.3%

0.6%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = .28, rho

= .24

Market neutrality in the ‘real world’

Using TASS data

2.5%

1.9%

1.3%

0.6%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = .28, rho

= .24

Market neutrality in the ‘real world’

Long Short Equity Funds

2.9%

2.2%

1.3%

0.6%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = .50, rho

= .37

Event driven style

3.1%

2.3%

1.5%

0.8%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = .20, rho

= .23

Dedicated Short Sellers

4.5%

3.4%

2.3%

1.1%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = -.91, rho =

-.61

Fixed income arbitrage

1.5%

1.1%

0.8%

0.4%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = 0.01, rho =

0.02

Funds of Hedge Funds

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Funds of Hedge Funds

Provides

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Funds of Hedge Funds

ProvidesDiversification – lower value at risk

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Funds of Hedge Funds

ProvidesDiversification – lower value at riskSmaller unit size of investment

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Funds of Hedge Funds

ProvidesDiversification – lower value at riskSmaller unit size of investmentProfessional management / Due

diligence

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Funds of Hedge Funds

ProvidesDiversification – lower value at riskSmaller unit size of investmentProfessional management / Due

diligenceAccess to otherwise closed funds

Hedge Fund 1 Hedge Fund 2 Hedge Fund 3

Fund of Funds

Institutions love FoF

Spectacular growth of Funds of Funds

2000: 15% of all Hedge funds were FoF2003: 18% of all Hedge funds were FoF2005: 27% of all Hedge funds were FoF

Institutional attraction of Funds of Funds

Risk management Due diligence

Funds of Funds

2.9%

2.2%

1.3%

0.6%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

S&P500 Returns0.2

0.6

0.8

0.4 Beta = .14, rho

= .22

Relationship to LIBOR

1.0%

0.8%

0.5%

0.3%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

LIBOR return0.2

0.6

0.8

0.4 Beta = 0.0, rho =

0.0

Fixed income arbitrage

2.0%

1.5%

1.0%

0.5%

Fu

nd

Retu

rns

0.2

0.4

0.6

0.8

LIBOR return0.2

0.6

0.8

0.4 Beta = -.02, rho =

-.05

Simple measures of tail risk exposure

Frequency of falling into lower decile for both fund and benchmark

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

-0.5 -0.3 -0.1 0.1 0.3 0.5

rho

Pro

bab

ility

MVN

MVt (3 df)

Independence an unrealistic benchmark

ConsiderMV Normal with

the same sample correlation

MV Student with 3 df

Simple measures of tail risk exposure

Frequency of falling into lower decile for both fund and benchmark

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

-0.5 -0.3 -0.1 0.1 0.3 0.5

rho

Pro

bab

ility

MVN

MVt (3 df)

Independence an unrealistic benchmark

ConsiderMV Normal with

the same sample correlation

MV Student with 3 df

0.24

0.0188

An example of ‘market neutrality’Fu

nd

Retu

rns

Market Returns0.2

0.2

0.4

0.6

0.8

0.6

0.8

0.4

1.5%

1.1%

0.8%

0.4%

Beta = .28, rho = .24

Assuming MVN returns

An example of ‘market neutrality’Fu

nd

Retu

rns

Market Returns0.2

0.2

0.4

0.6

0.8

0.6

0.8

0.4

1.5%

1.1%

0.8%

0.4%

Beta = .28, rho = .24

WW

LW

WLLL

LL should be 1.88% of sample assuming MVN

returns

Comparison with S&P500 Benchmark

Correlation with

benchmark

Binomial Crash

p-value (ind)

p-value (N)

p-value (t)

All Funds 0.28** 0 0 0

Funds of Funds 0.14** 0 0 0

Convertible Arbitrage 0.09** 0 0.033 0.840

Dedicated Short Bias -0.91** 0.997 0.112 0.838

Emerging Markets 0.66** 0 0.031 0.394

Equity Market Neutral 0.02 0.001 0.006 0.893

Event Driven 0.20** 0 0 0

Fixed Income Arbitrage 0.01 0.395 0.480 0.995

Global Macro 0.08 0.004 0.034 0.752

Long Short Equity 0.50** 0 0 0.006

Managed Futures -0.11** 0.563 0.127 0.999

Comparison with LIBOR Benchmark

Correlation with

benchmark

Binomial Crash

p-value (ind)

p-value (N)

p-value (t)

All Funds 0.00 1 1 1

Funds of Funds 0.01 1 1 1

Convertible Arbitrage 0.00 0 0 0.074

Dedicated Short Bias 0.07 0.006 0.031 0.432

Emerging Markets -0.17** 0.995 0.823 1

Equity Market Neutral 0.07** 0.148 0.567 1

Event Driven -0.04** 1 1 1

Fixed Income Arbitrage -0.05 0 0 0.007

Global Macro -0.03 0.849 0.756 0.999

Long Short Equity 0.00 1 1 1

Managed Futures -0.02 0.525 0.399 1

Logit Specification

Boyson, Stahel and Stulz [2006] suggest running logit regressions of whether a fund index crashes in a month upon the market return and a dummy for market crashes. A positive coefficient on the dummy indicates additional dependence during crashes.

Lacks power when run on a single index. We run the regressions on the cross-section.

Conclusions

Operational riskImportant role for due diligenceCharacterized by internal and

external conflicts of interestFinancial risk

Undiversifiable crash risk lurks in hedge fund returns, despite their seemingly light dependence in normal times.