Abstract

Conditional factor models allow both risk loadings and performance over a period to be a function of information available at the start of the period. Much of the literature to date has allowed risk loadings to be time-varying while imposing the assumption that conditional performance is constant. We develop a new methodology that allows conditional performance to be a function of information available at the start of the period. This methodology uses the Euler equation restriction that comes out of the factor model rather than the beta pricing formula itself. The Euler equation restrictions that we develop can be estimated using GMM. It is also possible to allow the factor returns to have longer data series than the mutual fund series as in Stambaugh (1997). We use our method to assess the conditional performance of funds in the Elton, Gruber and Blake (1996) mutual fund data set. Using dividend yield to track the business cycle, we find that conditional mutual fund performance moves with the business cycle, with all fund types except growth performing better in downturns than in peaks. The converse holds for growth funds, which do better in peaks than in downturns.

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