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Forecasting China's Crude Oil Futures Volatility: New Evidence from the MIDAS-RV Model and COVID-19 Pandemic

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Journal Resour Policy
Date 2021 Nov 22
PMID 34803209
Citations 1
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Abstract

In this study, we focus on the role of jumps and leverage in predicting the realized volatility (RV) of China's crude oil futures. We employ a standard mixed data sampling (MIDAS) modeling framework. First, the in-sample results indicate that the jump and leverage effects are useful in predicting the RV of Chinese crude oil futures. Second, the out-of-sample results suggest that jump has very significant predictive power at the one-day-ahead horizon while the leverage effect contains more useful information for long-term predictions. Moreover, our results are supported by a number of robustness checks. Finally, we find new evidence that the prediction model that considers the leverage effect has the best predictive power during the COVID-19 pandemic.

Citing Articles

Prediction of electricity energy consumption including COVID-19 precautions using the hybrid MLR-FFANN optimized with the stochastic fractal search with fitness distance balance algorithm.

Dalcali A, Ozbay H, Duman S Concurr Comput. 2022; 34(15):e6947.

PMID: 35539002 PMC: 9074447. DOI: 10.1002/cpe.6947.

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