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Global climate change and commodity markets: A hedging perspective

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  • Shanghui Jia
  • Xinhui Chen
  • Liyan Han
  • Jiayu Jin

Abstract

This paper aims to measure the tail‐risk dependence between climate change and commodity futures markets. We utilize Morgan Stanley Capital International Climate Change Index (CCI) to serve as a proxy indicator of the stock market climate change for examining the tail‐risk spillover effect among 16 major commodity futures. Using GARCH–Copula–CoVaR framework, we show that extreme climate change has a significant tail‐risk spillover effect on commodity futures markets, in which agricultural and energy futures are affected by climate change most. We then adopt the copula‐based generalized autoregressive conditional heteroskedasticity (GARCH) model to compute the optimal hedge ratio among each pair of CCI with commodity futures, which performs well economic advantages for all 16 commodities. Compared with hedging against commodity index, CCI has a more significant hedging effect on metal and energy subindex futures. Therefore, we finally suggest an effective hedging portfolio composed of CCI and subindex futures in a significant economic sense.

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  • Shanghui Jia & Xinhui Chen & Liyan Han & Jiayu Jin, 2023. "Global climate change and commodity markets: A hedging perspective," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1393-1422, October.
    • Handle: RePEc:wly:jfutmk:v:43:y:2023:i:10:p:1393-1422
    DOI: 10.1002/fut.22416
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    4. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
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