Modeling the Risk of Extreme Value Dependence in Chinese Regional Carbon Emission Markets

Abstract

In this study, we analyze the risk of extreme value dependence in Chinese regional carbon emission markets. After filtering the daily return data of six carbon markets in China using a generalized autoregressive conditional heteroscedasticity (GARCH) model, we obtain the standardized residual series. Next, the dependence structures in the markets are captured by the Copula function and the Extreme Value theory (EVT). We report high peaks, heavy tails and fluctuation aggregation in the logarithm return series of the markets, as well as significant dependent structures. There are significant extreme value risks in Chinese regional carbon markets, but the risks can be mitigated through appropriate portfolio diversification.

Study on Mechanisms Underlying Changes in Agricultural Carbon Emissions: A Case in Jilin Province, China, 1998–2018

“…At present, carbon emissions are a key reason for climate change [1]. China is not only the largest developing country in the world but also the largest country that emits carbon dioxide [2]. To reduce the negative impact of global warming and the deterioration of the ecological environment, China, as one of the important member states of the United Nations, at the 2009 Copenhagen Conference, made a commitment to reduce carbon dioxide emissions per unit of Gross Domestic Product (GDP) by 40%-45% from the 2005 level by 2020 [3].…”