Examining the overconfidence and overreaction in China?s carbon markets

This paper proposes a novel integrated approach combining structural vector autoregression model, impulse response function with event study to examine the overconfidence and overreaction in China's carbon markets. The structural vector autoregression model and impulse response function are adopted to measure the overconfidence and the relationship between market return and trading volume. The event study method is adopted to detect overreaction. We make the empirical test for the events of the United Nations Climate Change Conference and the proposal of China's carbon-neutral target. It is the first to explore the overconfidence and overreaction in China's carbon markets. The empirical results show that overconfidence exists in Beijing, Guangdong, Shanghai, Shenzhen, Tianjin, Chongqing, and Fujian carbon markets, while Hubei carbon market has no overconfidence. Carbon market transactions are positively correlated with market returns. Guangdong, Hubei, Shanghai, Shenzhen, Tianjin, and Chongqing carbon markets exist overreactions to the United Nations Climate Change Conference during 2014- 2019. Guangdong, Hubei, Shanghai, Shenzhen, and Chongqing carbon markets exist overreactions over China's carbon-neutral target. (c) 2022 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.

Automated summary

This paper proposes a novel integrated approach to examine the overconfidence and overreaction in China's carbon markets, and empirically tests the events of the United Nations Climate Change Conference and China's carbon-neutral target.