Turbulence in the Cross-Section: Predicting Factor Premia

Abstract

Theories that explain the size of factor premia are rare. We show that parameter uncertainty based on the turbulence withing each cross-section of factor portfolios produces a significant out-of-sample forecast for six out of seven tested Fama-French risk factors, yielding the best predictor among a variety of popular predictors in five of these cases. Therefore, one measure predicts all the premia solely based on information contained in its own cross-section.

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Working Paper
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