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The dynamics of precious metal markets VaR: A GARCHEVT approach

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  • Zhang, Zijing
  • Zhang, Hong-Kun

Abstract

The data analysis of the metal markets has recently attracted a lot of attention, mainly because the prices of precious metal are relatively more volatile than its historical trend. A robust estimate of extreme loss is vital, especially for mining companies to mitigate risk and uncertainty in metal price fluctuations. This paper examines the Value-at-Risk and statistical properties in daily price return of precious metals, which include gold, silver, platinum, and palladium, from January 11, 2000 to September 9, 2016. An advanced two stage approach which combines GARCH-type models with extreme value theory is implemented. In the first stage, the conditional variance is modeled by different rolling univariate GARCH-type models (GARCH, EGARCH and TGARCH) under the GED error assumption in the returns of precious metal markets and compare the same with other well-known models. In the second stage, extreme value approach is applied to capture the tail behavior of distribution for the extracted standardized residuals. In comparison with the dynamic VaRs of these precious metals, we find that gold has the most steady and the highest VaRs, followed by platinum and silver; on the other hand our results show that palladium has the most volatile VaRs. The backtesting result confirms that our approach is an adequate method in improving risk management assessments and hedging strategies in the high volatile metal markets.

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  • Zhang, Zijing & Zhang, Hong-Kun, 2016. "The dynamics of precious metal markets VaR: A GARCHEVT approach," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 14-27.
    • Handle: RePEc:eee:jocoma:v:4:y:2016:i:1:p:14-27
    DOI: 10.1016/j.jcomm.2016.10.001
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    2. Tripathi, Nitya Nand & Raj, Asha Binu & Tiwari, Aviral Kumar, 2022. "Do employees' salaries and board of director's remuneration impact gold demand?: An empirical study," Resources Policy, Elsevier, vol. 75(C).
    3. Bhatia, Vaneet & Das, Debojyoti & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Hasim, Haslifah M., 2018. "Do precious metal spot prices influence each other? Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 55(C), pages 244-252.
    4. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    5. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    6. Xin Chen & Zhangming Shan & Decai Tang & Biao Zhou & Valentina Boamah, 2023. "Interest rate risk of Chinese commercial banks based on the GARCH-EVT model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    7. Bao, Dun, 2020. "Dynamics and correlation of platinum-group metals spot prices," Resources Policy, Elsevier, vol. 68(C).

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