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Climate Risks and Forecastability of the Realized Volatility of Gold and Other Metal Prices

Author

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  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)

Abstract

We use variants of the Heterogeneous Autoregressive Realized Volatility (HAR-RV) model to examine the out-of-sample predictive value of climate-risk factors for the realized volatility of gold price returns as well as the realized volatility of other metal price returns (Copper, Palladium, Platinum, Silver). We estimate the HAR-RV models using not only ordinary least squares, but also we use three different popular shrinkage estimators. Our main finding is that climate-risk factors improve the accuracy of out-of-sample forecasts prices at a monthly and, in some cases, also at a weekly forecast horizon.

Suggested Citation

  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecastability of the Realized Volatility of Gold and Other Metal Prices," Working Papers 202172, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202172
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    References listed on IDEAS

    as
    1. Bonato, Matteo & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "A note on investor happiness and the predictability of realized volatility of gold," Finance Research Letters, Elsevier, vol. 39(C).
    2. Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).
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    Citations

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    Cited by:

    1. Yuqin Zhou & Shan Wu & Zhenhua Liu & Lavinia Rognone, 2023. "The asymmetric effects of climate risk on higher-moment connectedness among carbon, energy and metals markets," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Karmakar, Sayar & Gupta, Rangan & Cepni, Oguzhan & Rognone, Lavinia, 2023. "Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model," Resources Policy, Elsevier, vol. 82(C).
    3. Santino Del Fava & Rangan Gupta & Christian Pierdzioch & Lavinia Rognone, 2023. "Forecasting International Financial Stress: The Role of Climate Risks," Working Papers 202329, University of Pretoria, Department of Economics.
    4. Salisu, Afees A. & Olaniran, Abeeb & Lasisi, Lukman, 2023. "Climate risk and gold," Resources Policy, Elsevier, vol. 82(C).
    5. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Transition risk, physical risk, and the realized volatility of oil and natural gas prices," Resources Policy, Elsevier, vol. 81(C).

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    More about this item

    Keywords

    Climate Risks; Realized Volatility; Gold; Metals; Forecasting;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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