OUT-OF-SAMPLE STOCK RETURN PREDICTION USING HIGHER-ORDER MOMENTS

We analyze variance, skewness and kurtosis risk premia and their option-implied and realized components as predictors of excess market returns and of the cross-section of stock returns. We find that the variance risk premium is the only moment-based variable to predict S&P 500 index excess returns, with a monthly out-of-sample R 2 above 6% for the period between 2001 and 2014. Nonetheless, all aggregate moment-based variables are effective in predicting the cross-section of stock returns. Self-financed portfolios long on the stocks least exposed to the aggregate moment-based variable and short on the stocks most exposed to it achieve positive and significant Carhart 4-factor alphas and a considerably higher Sharpe ratio than the S&P 500 index, with positive skewness.