Which uncertainty is powerful to forecast crude oil market volatility? New evidence

Xiafei Li, Yu Wei, Xiaodan Chen, Feng Ma, Chao Liang and Wang Chen

International Journal of Finance & Economics, 2022, vol. 27, issue 4, 4279-4297

Abstract: This paper focuses on distinguishing the predictive power of five newly developed uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU), global geopolitical risk (GPR), US monetary policy uncertainty (MPU) and equity market volatility (EMV), on crude oil market volatility. We construct the extended GARCH‐MIDAS models to assess the forecasting ability of these indices and then compare them with four commonly used oil volatility drivers: oil supply, oil demand, oil speculation and interest rate. Firstly, the in‐sample analysis suggests that all uncertainty indices and traditional determinants have significant impacts on oil volatility. Secondly, the out‐of‐sample evaluations suggest that US MPU, EMV and EPU indices are more powerful than other predictors to improve the forecasting accuracy of crude oil volatility, and US EMV exhibits the best prediction ability. Then, we find that EPU and MPU indices are more effective in forecasting high volatility in crude oil market, while traditional determinants together with US EMV index are more helpful in predicting low oil volatility. Finally, the forecasts of bad oil volatility can be improved by all predictors except for GEPU index, while the forecasts of good oil volatility can only be enhanced by US MPU, EMV and EPU.

Date: 2022
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