Dynamic lead-lag relationship between Chinese carbon emission trading and stock markets under exogenous shocks

Using the non-parametric thermal optimal path method, we investigate the dynamic lead-lag relationship between carbon emission trading and stock markets in China, and further consider the impact of different types of exogenous shocks on the lead-lag relationship. The empirical results show that the stock market leads the carbon market on most trading days, and the relationship reverses when the mean values of carbon market return are significantly smaller than zero. In addition, the lead-lag relationships when the carbon market leads the high energy -consuming stock market sectors are more obvious. We also find that there exist significant heterogeneous effects of different types of exogenous shocks on the lead-lag relationship between the two markets, including government policy, the Sino-US trade war and the Covid-19 outbreak. These findings have the potential to help regulators understand the interrelationship between components of the financial market, and be of great value for investors to optimize portfolio allocation by incorporating carbon assets into the portfolio.

Automated summary

Using the non-parametric thermal optimal path method, this study examines the dynamic lead-lag relationship between carbon emission trading and stock markets in China, taking into account the impact of different types of exogenous shocks on this relationship. The empirical findings show that the stock market tends to lead the carbon market, except when the mean values of carbon market return are significantly smaller than zero. The lead-lag relationship is more pronounced when the carbon market leads the high energy-consuming stock market sectors. Furthermore, the study identifies significant heterogeneous effects of different types of exogenous shocks on the lead-lag relationship, including government policy, the Sino-US trade war, and the Covid-19 outbreak.