Abstract
This article analyzes the risk characteristics for various hedge fund strategies specializing in fixed income instruments. Because some fixed income hedge fund strategies have exceptionally high autocorrelations in reported returns and this is taken as evidence of return smoothing, we first develop a method to completely eliminate any order of serial correlation across a wide array of time series processes. Once this is complete, we determine the underlying risk factors to the adjusted hedge fund returns and examine the incremental benefit attained from using nonlinear payoffs relative to the more traditional linear factors. The hedge fund indices have a very strong exposure to high-yield credit. In general, we find a marginal benefit to using the nonlinear risk factors in terms of the ability to explain reported returns. Finally, we examine the benefit of using various factor structures for estimating the value-at-risk of the hedge funds. We find that for some of the hedge fund strategies, downside risk estimates can be quite substantial. <b>TOPICS:</b>Factor-based models, analysis of individual factors/risk premia
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