Risk management for hedge funds AQF 2005 Nicolas Papageorgiou - - PowerPoint PPT Presentation

Risk management for hedge funds

AQF 2005 Nicolas Papageorgiou

Outline

• VaR and drawbacks
• Nonlinearities
• Credit risk and liquidity

Can risk management be a source of alpha

• Consider fund with E(r)= 10% and volatility=70%

– Not very interesting

• Consider risk management strategy that

eliminates returns lower than -20%

• Truncation of distribution will double expected

returns and reduce volatility

• But what is the cost?
• According to BS – 15% of the portfolio
• Risk management can add value and hence be

a source of alpha

Why not VaR

• Cannot capture the spectrum of risks that hedge funds cover
• VaR is a purely statistical measure with no economic interpretation

– It is a static snapshot of marginal distribution of a portfolio’s profit-and- loss.It does no capture

• Liquidity risk
• Event risk
• Credit risk
• Factor exposures
• Time varying risks due to dynamic trading strategies that may be

systematically keyed to market conditions (contrarian, short volatility, credit spread strategies

• VaR difficult to estimate for rare events
• rare events.doc
• VaR is an unconditional measure of risk

Dynamic Risk-Analytics

• Can static measures capture the risk of

dynamic strategies

• Example of CDP

CDP returns (92-99)

2721.3% 367.1% 59.9% 100% Correlation w SP500 6/96 36/96 # negative months 1.94 0.98 Annual Sharpe 27.0% 14.0% Max

• 18.3%
• 8.9%

Min 5.8% 3.6% Std.dev 3.7% 1.4% Monthly mean CDP S&P500

What is CDP’s strategy

• Short OTM S&P500 put options on each

monthly expiration date for maturities < 3 months and with strikes approx. 7% OTM.

• Would you be willing to pay high fees for

this strategy?

• Managers can easily use this strategy to

increase returns…

Dynamic strategies

• Managers can also replicate option like

payoffs by using leverage on momentum based strategies

– Voir CTAs and lookback straddles

Non-linearities

• Phase locking behavior

– Uncorrelated actions suddenly become synchronized

• How do we capture this « phase locking »

behavior

• Phase locking behavior.doc

Non-linearities

• Let us assume p=0.0001
• Generally expected return (and volatility)

will not depend on Z.

• What if volatility of Z is much greater than

those of idiosyncratic risk and market factor?

• Then Z will dominate expected returns

when I=1.

• correlation.doc

Non-linearities

• How about calculating corelation using

unconditional variances?

• Unconditional correlation.doc

Non-linearities

• Assymetric sensitivity to the S&P500.
• Different beta for up market and down

markets

Liquidity and credit risk

• Autocorrelation as an indication of liquidity

exposure

– The more efficient, the less predictable…

Other readings

• Risk and portfolio decisions involving

hedge funds, Agarwal and Naik 2004.