Hedge Fund Market Neutral Strategies: Distinguishing Financial and Operational Risk Factors

1
Hedge Fund Market Neutral Strategies
Distinguishing Financial and Operational Risk
Factors

• Stephen J. Brown
• NYU Stern

The Joint 14th Annual PBFEA and 2006 Annual FeAT
Conference   ???????????????? 2006?????????????
2
Distinguishing operational and financial risk

• Historical perspective
• Operational risk
• Characterized by conflicts of interest
• Financial risk
• The myth of market neutrality
• Robust measure of tail risk neutrality
• Conclusion

3
The History of Hedge Funds

• The first hedge fund Alfred Winslow Jones (1949)
• Limited Partnership (exempt from 40 Act)
• Long-short strategy
• 20 of profit, no fixed fee
• Used 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)

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Institutional concern about risk

• Fiduciary guidelines imply concern for risk
• Financial risk
• Operational risk
• Institutional demand
• Growing popularity of market neutral styles
• Explosive growth of funds of funds
• Demand for market neutral funds of funds

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Operational Risk
Hedge fund failure is highly predictable
Source Tremont TASS (Europe) Limited
6
Measuring operational risk

• SEC registration requirement (Feb 2006)
• 2270 of TASS Funds that registered
• Had better past performance
• Had larger assets under management
• 15.8 had prior legal/regulatory problems
• What are the correlates of operational risk?

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Correlates of operational risk
Problem Funds Problem Funds Problem Funds Non-Problem Funds Non-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
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External conflicts
Problem funds Problem funds Non problem funds Non problem funds
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
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Internal conflicts
Problem funds Problem funds Non problem funds Non problem funds
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
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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
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Financial Risk
Source Elton and Gruber 1995. Risk is measured
relative to the standard deviation of the average
stock
12
Financial Risk
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Caught by the tail

• SP500 returns at Treasury Bill risk
• Most new funds claim to be market neutral
• Zero correlation with benchmark
• Zero correlation is not a strategy
• Zero correlation is an outcome of a strategy
• These strategies fail in liquidity crises
• Risk is considerably understated
• New concept tail risk neutrality

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A market neutral strategy
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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.

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An example of market neutrality
1.5
0.8
1.1
0.6
Fund Returns
0.8
0.4
0.4
0.2
0.2
0.6
0.8
0.4
Market Returns
Beta .28, rho .24
Assuming MVN returns
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Market neutrality in the real world
2.5
0.8
1.9
0.6
Fund Returns
1.3
0.4
0.6
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta .28, rho .24
Using TASS data
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Market neutrality in the real world
2.5
0.8
1.9
0.6
Fund Returns
1.3
0.4
0.6
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta .28, rho .24
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Long Short Equity Funds
2.9
0.8
2.2
0.6
Fund Returns
1.3
0.4
0.6
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta .50, rho .37
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Event driven style
3.1
0.8
2.3
0.6
Fund Returns
1.5
0.4
0.8
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta .20, rho .23
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Dedicated Short Sellers
4.5
0.8
3.4
0.6
Fund Returns
2.3
0.4
1.1
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta -.91, rho -.61
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Fixed income arbitrage
1.5
0.8
1.1
0.6
Fund Returns
0.8
0.4
0.4
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta 0.01, rho 0.02
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Funds of Hedge Funds
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Funds of Hedge Funds

• Provides

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Funds of Hedge Funds

• Provides
• Diversification lower value at risk

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Funds of Hedge Funds

• Provides
• Diversification lower value at risk
• Smaller unit size of investment

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Funds of Hedge Funds

• Provides
• Diversification lower value at risk
• Smaller unit size of investment
• Professional management / Due diligence

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Funds of Hedge Funds

• Provides
• Diversification lower value at risk
• Smaller unit size of investment
• Professional management / Due diligence
• Access to otherwise closed funds

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Institutions love FoF

• Spectacular growth of Funds of Funds
• 2000 15 of all Hedge funds were FoF
• 2003 18 of all Hedge funds were FoF
• 2005 27 of all Hedge funds were FoF
• Institutional attraction of Funds of Funds
• Risk management
• Due diligence

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Funds of Funds
2.9
0.8
2.2
0.6
Fund Returns
1.3
0.4
0.6
0.2
0.2
0.6
0.8
0.4
SP500 Returns
Beta .14, rho .22
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Relationship to LIBOR
1.0
0.8
0.8
0.6
Fund Returns
0.5
0.4
0.3
0.2
0.2
0.6
0.8
0.4
LIBOR return
Beta 0.0, rho 0.0
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Fixed income arbitrage
2.0
0.8
1.5
0.6
Fund Returns
1.0
0.4
0.5
0.2
0.2
0.6
0.8
0.4
LIBOR return
Beta -.02, rho -.05
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Simple measures of tail risk exposure

• Independence an unrealistic benchmark
• Consider
• MV Normal with the same sample correlation
• MV Student with 3 df

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Simple measures of tail risk exposure

• Independence an unrealistic benchmark
• Consider
• MV Normal with the same sample correlation
• MV Student with 3 df

0.0188
0.24
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An example of market neutrality
1.5
0.8
1.1
0.6
Fund Returns
0.8
0.4
0.4
0.2
0.2
0.6
0.8
0.4
Market Returns
Beta .28, rho .24
Assuming MVN returns
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An example of market neutrality
1.5
0.8
1.1
0.6
WW
LW
Fund Returns
0.8
0.4
0.4
0.2
WL
LL
0.2
0.6
0.8
0.4
LL should be 1.88 of sample assuming MVN returns
Market Returns
Beta .28, rho .24
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Comparison with SP500 Benchmark
Correlation with benchmark Binomial Crash Binomial Crash Binomial Crash Binomial Crash
Correlation with benchmark 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
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Comparison with LIBOR Benchmark
Correlation with benchmark Binomial Crash Binomial Crash Binomial Crash Binomial Crash
Correlation with benchmark 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
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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.

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Conclusions

• Operational risk
• Important role for due diligence
• Characterized by internal and external conflicts
  of interest
• Financial risk
• Undiversifiable crash risk lurks in hedge fund
  returns, despite their seemingly light dependence
  in normal times.