A conditional approach to hedge fund risks
AbstractThis article applies a two-step conditional Bayesian approach to hedge fund risk. First, a mixture or-two normal distributions is estimated for a core asset; one distribution being identified as linked to a "quiet" regime and the other to a "hectic" regime. The conditional probabilities of each regime are then inferred and a mixture of distributions is deduced for peripheral assets. The core asset is alternatively chosen as the S&P index or the Baa/Treasuries yield spread whereas the peripheral assets are chosen to be the major hedge funds strategies over the period 1990-2004. This methodology has several advantages given specific features of hedge funds returns, notably non-linear exposure to standard assets returns and short sample history. Significant changes in the distribution (mean and standard deviation) of hedge fund returns are identified across regimes. Results are less clear-cut for the correlation with standard assets, as modifications can be imputed to a certain extent to a form of selection bias. An application of this methodology to stress tests on hedge funds portfolios is presented.
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Bibliographic InfoPaper provided by Paris Dauphine University in its series Economics Papers from University Paris Dauphine with number 123456789/682.
Date of creation: 2006
Date of revision:
Publication status: Published in Journal of Alternative Investments, 2006, Vol. 9, no. 1. pp. 64-77.Length: 13 pages
Risk; Standard deviations; Hedging (finance); Mutual funds; Hedge funds; Finance;
Find related papers by JEL classification:
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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