Volatility predictability in crude oil futures: Evidence based on OVX, GARCH and stochastic volatility models

• Published in: Energy strategy reviews Vol. 50; p. 101209
• Main Authors: Zhang, Zheng, Raza, Muhammad Yousaf, Wang, Wenxue, Sui, Lu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2023; Elsevier
• Subjects: Crude oil future; GARCH-type model; Stochastic volatility model; Volatility estimation; Volatility forecast; C53; GARCH-type model; C32; Q47; Volatility estimation; C58; E37; Stochastic volatility model; Crude oil future; G17; Volatility forecast
• ISSN: 2211-467X; 2211-467X
• DOI: 10.1016/j.esr.2023.101209

The paper examines the volatility predictive ability of the CBOE crude oil volatility index (OVX), GARCH and Stochastic Volatility Models in the crude oil market. Specifically, the dynamics of two major crude oil pricing benchmarks — Brent in Europe and WTI in America are compared. OVX index is able to provide the optimal forecast for the volatility of Brent’s future. The GJR-GARCH model outperforms its competition volatility models in both oil markets. It also reveals that WTI exhibits a faster and stronger response to market shocks compared to Brent oil. Most importantly, the predictability exhibit consistent and convincing results during remarkable events: the 2014 oil price decline, the 2020 coronavirus pandemic, and the 2022 Russian–Ukraine war. In practice, the paper contributes to portfolio strategy construction and investment risk management. •WTI has a quicker and stronger response than Brent, and its variance of WTI is more persistent.•WTI has a stronger leverage effect than Brent and comparatively shows more financial characteristics.•OVX index provides the optimal forecast for the volatility of Brent’s future.•In the volatility forecasting of the GARCH-type models, the GJR-GARCH model is the best for both oil futures.