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Predicting gold volatility: Exploring the impact of extreme risk in the international commodity market

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  • Tang, Yusui
  • Zhong, Juandan

Abstract

This paper mainly examines the performance of the tail risk (TR) constructed by 19 sub-categories of commodity price indices for predicting gold futures market volatility. Under the framework of the AR model, we compared the predictive capabilities of AR-type models incorporating the TR indicator as an additional explanatory variable against the AR benchmark model without the TR indicator. Our findings reveal that the incorporation of the TR indicator significantly improves the predictive accuracy of the gold futures volatility model. Notably, this enhancement is particularly pronounced during periods of heightened volatility.

Suggested Citation

  • Tang, Yusui & Zhong, Juandan, 2023. "Predicting gold volatility: Exploring the impact of extreme risk in the international commodity market," Finance Research Letters, Elsevier, vol. 58(PB).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pb:s1544612323008632
    DOI: 10.1016/j.frl.2023.104491
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    References listed on IDEAS

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