The Information Content of OVX for Crude Oil Returns Analysis and Risk Measurement: Evidence from the Kalman Filter Model

Abstract

Crude oil volatility index (OVX) is a new index published by Chicago Board Option Exchange since 2007. In recent years it emerged as an important alternative measure to track and analyze the volatility of future oil prices. In this paper we firstly model and analyze the dynamic relationship between OVX changes and future crude oil price returns with time-varying coefficients, modeled using the Kalman filter, in the regression models. Empirical results show a weak negative relationship between OVX changes and future crude oil price returns movement, and extremely high/low levels of OVX cannot predict future positive/negative returns well. Secondly, this paper explores whether OVX can predict future realized volatility of crude oil price returns. The empirical findings suggest that OVX serves as an unbiased but not an efficient estimate of the future realized volatility and it includes information of the future realized volatility. Finally the incorporation of information of OVX in measuring market risk is analyzed. The empirical result indicates that Kalman filter based model provides the improved performance than the linear regression model in terms of forecasting accuracy for realized volatility prediction and the reliability for VaR estimate.