DP12760 | Expected Stock Returns and the Correlation Risk Premium

Publication Date


JEL Code(s)


Programme Area(s)



We show that the correlation risk premium can predict future market excess returns in-sample and out-of-sample for long horizons and contains information that is non-redundant relative to the variance risk premium. To exploit this predictability, we develop a novel estimation methodology that uses contemporaneous increments of option-implied variables, efficiently removing any lag in estimation of variance and correlation risk betas. The methodology leads to considerable out-of-sample predictability, with an R2 of 7.0% at an annual horizon, and substantial economic gains for investors. The results are supported by a multi-asset general-equilibrium model in which variance and correlation risk are endogenously priced.