Systemic risk in China new energy stock markets

Purpose - The purpose of the paper is to assess the systemic risk in the new energy stock markets of China. Design/methodology/approach - This paper first uses the VaR method to study individual stock market risks. It then introduces the DCC model to capture the dynamic conditional correlation among the new energy stock markets. Findings - The paper shows a generally upward trend of the stock market risk over time in the recent decade. Among all the markets considered, the solar power market demonstrates the highest risk, closely followed by the wind power market, while the hydropower market exhibits the lowest risk. Furthermore, the average dynamic conditional correlations among the new energy markets stay high during the period under investigation though daily correlations vary and significantly declined in 2020. Originality/value - To the best of the authors’ knowledge, this paper is the first of its kind to study the systemic risk within the new energy stock market context. In addition, it not only investigates individual new energy stock market risks but also examines the dynamic linkages among those markets, thus providing comprehensive and unprecedented evidence of systemic risk in China new energy markets, which have useful implications for both regulators and investors.