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Cryptocurrency uncertainty and volatility forecasting of precious metal futures markets

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  • Wei, Yu
  • Wang, Yizhi
  • Lucey, Brian M.
  • Vigne, Samuel A.

Abstract

Several common properties shared by cryptocurrencies and precious metals, such as safe haven, hedge and diversification for risk assets, have been widely discussed since Bitcoin was created in 2008. However, no studies have explored whether cryptocurrency market uncertainties can help to explain and forecast volatilities in precious metal markets. By using the GARCH-MIDAS model incorporating cryptocurrency policy and price uncertainty, as well as several other commonly used uncertainty measures, this paper compares the in-sample impacts and out-of-sample predictive abilities of these uncertainties on volatility forecasts of COMEX gold and silver futures markets. The in-sample results demonstrate the significant impacts of cryptocurrency uncertainty on the volatilities of precious metal futures markets, and the out-of-sample evidence further confirms the superior predictive power of cryptocurrency uncertainty on volatility forecasting of the precious metal market. Our conclusions are robust through various model evaluation approaches based not only on predicting errors but also on forecasting directions across different forecasting time horizons.

Suggested Citation

  • Wei, Yu & Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A., 2023. "Cryptocurrency uncertainty and volatility forecasting of precious metal futures markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
  • Handle: RePEc:eee:jocoma:v:29:y:2023:i:c:s2405851322000629
    DOI: 10.1016/j.jcomm.2022.100305
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    6. Jia, Boxiang & Shen, Dehua & Zhang, Wei, 2024. "Bitcoin market reactions to large price swings of international stock markets," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 72-88.
    7. Yuan Li & Bingqiao Luo & Qian Wang & Nuo Chen & Xu Liu & Bingsheng He, 2024. "A Reflective LLM-based Agent to Guide Zero-shot Cryptocurrency Trading," Papers 2407.09546, arXiv.org.
    8. Li, Wei & Zhang, Junchao & Cao, Xiangye & Han, Wei, 2024. "Is the prediction of precious metal market volatility influenced by internet searches regarding uncertainty?," Finance Research Letters, Elsevier, vol. 62(PB).
    9. John Kingsley Woode & Anokye M. Adam & Peterson Owusu Junior & Anthony Adu-Asare Idun, 2024. "Industrial metal and cryptocurrency market plummets: Interdependence, policy uncertainty, or investor sentiments?," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 51(4), pages 1001-1040, December.
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    12. Joo, Young C. & Park, Sung Y., 2023. "Quantile connectedness between cryptocurrency and commodity futures," Finance Research Letters, Elsevier, vol. 58(PC).
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    More about this item

    Keywords

    Cryptocurrency uncertainty; Precious metal; Volatility forecasting; Model evaluation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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