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Capturing Risks of Non-transparent Hedge Funds
Jan 1, 2010
We present a model that captures risks of hedge funds only using their historical performance as input.
This statistical model is a multivariate distribution where the marginals derive from an AR(1)/AGARCH(1,1) process with t5 innovations, and the dependency is a grouped-t copula. The process captures all relevant static and dynamic characteristics of hedge fund returns, while the copula enables us to go beyond linear correlation and capture strategy-specific tail dependency. We show how to estimate parameters and then successfully backtest our model and some peer models using 600+ hedge funds.
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