Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investmentsand between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations.We would like to thank Bing Liang, the editor, an anonymous referee, and participants in finance seminar at the University of Massachusetts and the 2006 meeting of European Financial Management for their helpful comments. We remain responsible for any errors.

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This study uses a set of return‐based factors to explore market (return and volatility) timing ability of commodity trading advisors (CTAs). Unlike previous research, we use return‐based factors that are related to the futures markets in which most CTAs trade. This leads to higher explanatory power for our multifactor model. Our approach allows us to test for the presence of market timing in multiple markets. Accordingly, we are able to identify the markets in which CTAs may have market timing ability. We find that systematic CTAs are generally more skilled at market timing than discretionary CTAs, with the latter having slightly better overall risk‐adjusted performance during our study period: January 1994 to December 2004. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:1067–1099, 2009