Jumps and oil futures volatility forecasting: a new insight

Feng Ma, Chao Liang, Qing Zeng and Haibo Li

Quantitative Finance, 2021, vol. 21, issue 5, 853-863

Abstract: This study designs the Markov-switching (MS) mixed data sampling (MIDAS) models and then explores the effects of intraday and interday jumps on oil futures price realized volatility. The in-sample estimates show that the current realized volatility and jumps have significantly positive impacts on oil futures price volatility using MIDAS models. However, the effects of the jumps are mixed when using MS-MIDAS models. Out-of-sample evaluations show that our proposed model, which includes continuous volatility and jumps based on the Time-of-Day volatility pattern (TOD) test combined with the Markov-switching MIDAS model (MS-MIDAS-TOD), exhibits a higher predictive ability for forecasting one-day-ahead oil futures volatility. Moreover, we further find that the improved results of this model remain significant over medium-term and long-term horizons and can also outperform a simple combination forecast.

Date: 2021
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Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:taf:quantf:v:21:y:2021:i:5:p:853-863

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DOI: 10.1080/14697688.2020.1805505

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