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Climate risks and predictability of the trading volume of gold: Evidence from an INGARCH model

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  • Karmakar, Sayar
  • Gupta, Rangan
  • Cepni, Oguzhan
  • Rognone, Lavinia

Abstract

We investigate whether text-based physical or transition climate risks forecast the daily volume of gold trade contracts. Given the count-valued nature of gold volume data, we employ a log-linear Poisson integer-valued generalized autoregressive conditional heteroskedasticity (IN-GARCH) model with a climate-related covariate. We detect that physical risks have a significant predictive power for gold volume at 5- and 22-day-ahead horizons. Additionally, from a full-sample analysis, it emerges that physical risks positively relate with gold volume. Combining these findings, we conclude that gold hedges physical risks at 1-week and 1-month horizons. Similar results hold for platinum and palladium, but not for silver.

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  • 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).
    • Handle: RePEc:eee:jrpoli:v:82:y:2023:i:c:s0301420723001460
    DOI: 10.1016/j.resourpol.2023.103438
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    Cited by:

    1. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    2. 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.
    3. Kejin Wu & Sayar Karmakar, 2023. "GARHCX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables," Papers 2308.13346, arXiv.org.

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    More about this item

    Keywords

    Climate risks; Precious metals; Forecasting; Trading volumes; Count data; INGARCH;
    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
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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