Reexamining Financial and Economic Predictability with New Estimators of Realized Variance and Variance Risk Premium

Abstract

This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from new parametric and semiparametric asymmetric extensions of the heterogeneous autoregressive model. Using these new specifications, we determine that the equity variance risk premium is a predictor of future excess stock returns, whereas conditional variance predicts them only for long horizons. Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional variance is determined to be the only predictor of economic activity for all horizons. Before the global financial crisis period, the new parametric asymmetric specification of the heterogeneous autoregressive model gains predictive power in comparison to previous work in the literature. However, the new time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil.

Keywords: Net Measures, Nonparametric Methods, Predictability, Realized Variance, Variance Risk Premium, VIX

JEL Classification: C22, C51, C52, C53, C58, G17