International commodity-market tail risk and stock volatility

Juandan Zhong, Huaigang Long, Feng Ma and Jiqian Wang

Applied Economics, 2023, vol. 55, issue 49, 5790-5799

Abstract: Using the method of, this study constructs a tail risk predictor of the international commodity market to forecast US stock volatility. The in-sample results show that tail risk contains significant interpretive ability for stock volatility. Being of our interest, the tail risk predictor can successfully predict the US stock volatility from both statistical and economic viewpoints. The results of controlling 12 popular macroeconomic variables suggest that tail risk contains incremental information for stock volatility. To further confirm our findings, we examine the forecasting performance of the tail risk predictor for 12 industrial portfolios.

Date: 2023
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DOI: 10.1080/00036846.2022.2140764

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