The Dynamics of the Variance Risk Premium: Refining Volatility Forecasts and Portfolio Returns

Abstract: In this paper, we investigate the dynamics of the variance risk premium and whether it can be used to achieve incremental predictability of future volatility on the S&P 500 index. Previous studies have focused on the usefulness of implied volatility in volatility forecasting. However, these studies do not take into account the distortion in implied volatility caused by the risk premium investors demand, despite that such a distortion has been suspected for decades. We introduce a parsimonious model that accounts for the time varying risk premium embedded in implied volatility. We come up with the instantaneous variance premium (IVP) variable designed to capture the time variability of the variance risk premium. Our proposed forecasting model is able to outperform prevailing models both in-sample and out-of-sample. A trading strategy with exposure to variance risk is created based on the results, and it shows that the novel variables are able to capture the dynamic properties of the variance risk premium. The trading strategy shows an improved performance compared to a benchmark, which provides evidence that the IVP variable can be used to accurately predict the variance risk premium. Our analysis uncovers useful information about the behavior of the VRP both in the context of volatility forecasting and portfolio optimization.