Research and publications
A Comparison of Alternative Approaches for Determining the Downside Risk of Hedge Fund Strategies
This paper compares a number of different approaches for determining the Value at Risk (VaR) and Expected Shortfall (ES) of hedge fund investment strategies. The authors compute VaR and ES through completely model-free methods, as well as through mean/variance and distribution model-based methods. Among the models considered certain specifications can technically address autocorrelation, asymmetry, fat tails, and time-varying variances which are typical characteristics of hedge fund returns. They find that conditional mean/variance models coupled with appropriate distributional assumptions improve their ability to predict VaR, 1% VaR in particular. They also find that the goodness of ES prediction models is primarily influenced by the distribution model rather than the mean/variance specification. A revisited version of this paper was published in the March 2009 issue of the Journal of Futures Markets.
Author(s):
Daniel Giamouridis and Ioanna Ntoula
Summary:
This paper compares a number of different approaches for determining the Value at Risk (VaR) and Expected Shortfall (ES) of hedge fund investment strategies. The authors compute VaR and ES through completely model-free methods, as well as through mean/variance and distribution model-based methods. Among the models considered certain specifications can technically address autocorrelation, asymmetry, fat tails, and time-varying variances which are typical characteristics of hedge fund returns. They find that conditional mean/variance models coupled with appropriate distributional assumptions improve their ability to predict VaR, 1% VaR in particular. They also find that the goodness of ES prediction models is primarily influenced by the distribution model rather than the mean/variance specification. A revisited version of this paper was published in the March 2009 issue of the Journal of Futures Markets.
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Register/Log in| Type : | Working paper |
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| Date : | 01/08/2007 |
| Keywords : |
Performance Measurement |
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