This paper analyzes the risk characteristics for various hedge fund strategies specializing in fixed income instruments. Because 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 autocorrelation process across a wide array of time series processes. Once this is complete, we determine the underlying risk factors to the “true” hedge fund returns and examine the incremental benefit attained from using nonlinear payoffs relative to the more traditional linear factors. For a great many of the hedge fund indices we find the strongest risk factor to be equivalent to a short put position on high-yield debt. In general, we find a moderate benefit to using the nonlinear risk factors in terms of the ability to explain reported returns. However, in some cases this fit is not stable even over the in-sample period. Finally, we examine the benefit to using various factor structures for estimating the value-at-risk of the hedge funds. We find, in general, that using nonlinear factors slightly increases the estimated downside risk levels of the hedge funds due to their option-like payoff structures.