Evaluating Fixed Income Fund Performance with Stochastic Discount Factors

Abstract

We evaluate the performance of fixed income mutual funds using stochastic discount factors from continuous-time term structure models. Time-aggregation of the models for discrete returns generates additional empirical factors, and these factors contribute significant explanatory power to empirical the models. We provide the first conditional performance evaluation for US fixed income mutual funds, conditioning on a variety of discrete ex ante characterizations of the state of the term structure and the economy. During 1985-1999 fixed income funds returned less on average than passive benchmarks that don't pay expenses, but not in all economic states. Fixed income funds typically do poorly when short term interest rates or industrial capacity utilization rates are high, and offer higher returns when quality-related credit spreads are high. We find more heterogeneity across fund styles than across characteristics-based fund groups. Mortgage funds under perform a GNMA index in all economic states. These excess returns are reduced, and typically become insignificant, when we adjust for risk using the stochastic discount factors.