Affiliation:
1. School of Statistics and Mathematics Central University of Finance and Economics Beijing China
2. School of Economics and Management BeiHang University Beijing China
3. Department of Digital Economics Yanqi Lake Beijing Institute of Mathematical Sciences and Applications Beijing China
Abstract
AbstractThis 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.
Funder
China Postdoctoral Science Foundation
National Natural Science Foundation of China
Subject
Economics and Econometrics,Finance,General Business, Management and Accounting,Accounting
Cited by
1 articles.
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