Аннотация:Hedge fund managers are largely free to pursue dynamic trading strategies, and standard static performance appraisal is no longer accurate for evaluating hedge funds. Accordingly, this article presents some new ways of analyzing hedge fund strategies following a dynamic linear regression model. Statistical residual diagnostics are considered to assess the appropriate use of the model. The authors unveil dynamic alphas and betas for each investment style during the period of January 1994 to December 2008.They examine the in-sample goodness-of-fit and out-of-sample predictability on hedge fund performance. By simulating a hypothetical trading strategy, they demonstrate that the model-based predictability helps to implement a profitable fund selection process. Finally, timing skills can be directly examined with a dynamic model; they find significant evidence for market timing, volatility timing, and liquidity timing, which is consistent with the timing literature about hedge funds. TOPICS:Real assets/alternative investments/private equity, style investing, statistical methods, performance measurement
