Examining the predictive information of CBOE OVX on China’s oil futures volatility: Evidence from MS-MIDAS models

Xinjie Lu, Feng Ma, Jiqian Wang and Jianqiong Wang

Energy, 2020, vol. 212, issue C

Abstract: This study evaluates whether CBOE crude oil volatility index (OVX) owns forecasting ability for China’s oil futures volatility using Markov-regime mixed data sampling (MS-MIDAS) models. In-sample empirical result shows that, OVX can significantly lead to high future short-term, middle-term and long-term volatilities with regard to Chinese oil futures market. Moreover, our proposed model, the Markov-regime MIDAS with including the OVX (MS-MIDAS-RV-OVX), significantly outperforms the MIDAS and other competing models. Unsurprising results further confirm that OVX indeed contain predictive information for oil realized volatility (especially significant and robust in middle-term and long-term horizons) and regime switching is useful to deal with the structural break within the energy market. We carry out economic value analysis and discuss OVX’s asymmetric effects concerning different trading hours and good (bad) OVX, and find OVX performs better in day-time trading hours and the good OVX is more predictive for the oil futures RV than the bad OVX. The further discussion also confirms our previous conclusions are robust during the highly volatile period of the COVID-19 pandemic.

Keywords: CBOE OVX; China’s oil futures; Volatility forecasting; Regime Switching; MIDAS model (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (36)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:212:y:2020:i:c:s0360544220318508

DOI: 10.1016/j.energy.2020.118743

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