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Title: Moment conditions and time-varying risk premia Authors:  Dennis Umlandt - University of Innsbruck (Austria) [presenting]
Abstract: A novel approach is proposed for estimating linear factor pricing models with dynamic risk premia based on a generalized method of moment framework. Time-varying risk premia follow an updating scheme driven by the influence function of the conditional moment criterion function at time $t$. The most informative moment for inferring risk premium dynamics stems from the cross-sectional pricing equation that is estimated in the second stage of the popular Fama-MacBeth regression approach. In addition, the procedure can accommodate time series predictors and enhance risk premium forecasts based on errors in current moment conditions. Consistency and asymptotic normality of the generalized method of moments estimators are established. The performance of the method is investigated through a Monte Carlo study. An application to a dynamic version of the Fama-French 3-Factor model reveals factor risk premia dynamics which cannot be explained by typical time series predictors.