CLIMATE RISKS AND PREDICTABILITY OF COMMODITY RETURNS AND VOLATILITY: EVIDENCE FROM OVER 750 YEARS OF DATA

Jacobus Nel (), Rangan Gupta, Mark Wohar and Christian Pierdzioch
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Jacobus Nel: Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa

Climate Change Economics (CCE), 2024, vol. 15, issue 04, 1-40

Abstract: We analyze whether metrics of climate risks, as captured primarily by changes in temperature anomaly and its stochastic volatility (SV), can predict returns and volatility of 25 commodities, covering the overall historical period of 1258 to 2021. To this end, we apply a higher-order nonparametric causality-in-quantiles test to not only uncover potential in-sample predictability in the entire conditional distribution of commodity returns and volatility but also to account for nonlinearity and structural breaks which exist between commodity returns and the metrics of climate risks. We find that, unlike in the misspecified linear Granger causality tests, climate risks do predict commodity returns and volatility, though the impact on the latter is stronger, in terms of the coverage of the conditional distribution. Insights from our findings can benefit academics, investors, and policymakers in their decision-making.

Keywords: Climate risks; commodities; returns and volatility predictions; higher-order nonparametric causality-in-quantiles test (search for similar items in EconPapers)
JEL-codes: C22 C53 Q02 Q54 (search for similar items in EconPapers)
Date: 2024
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Working Paper: Climate Risks and Predictability of Commodity Returns and Volatility: Evidence from Over 750 Years of Data (2022)
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DOI: 10.1142/S2010007824500039

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