Volatility Predictability in Crude Oil Futures: Evidence Based on OVX, GARCH and Stochastic Volatility Models

This paper explores the predictive ability of volatility in the crude oil market. A comparison in the CBOE crude oil volatility index (OVX), GARCH and Stochastic Volatility Models are employed to investigate the forecasting performance. The daily price dataset, spanning from 2010 to 2022, captures significant oil price drops in the recent decade: the oil price decline in 2014, the coronavirus pandemic, and the Russian-Ukraine war. GARCH-type models are employed to test the leverage effect in crude oil, while stochastic volatility models examine the series dependence and heavy-tailed distribution. The findings reveal the facts that WTI exhibits a faster and stronger response compared to Brent during the period of the Covid-19 pandemic and the Russian-Ukraine War. Among the six loss functions, the GJR-GARCH model outperforms its competitors in five of them. The OVX index proves to be optimal for Brent’s prediction. In the context of an unstable global politics and economic environment, governments can benefit from accurate predictions in the crude oil market to mitigate losses and manage geopolitical risks.