Measuring the connectedness of new energy stock markets of China: new evidence and implications

Purpose The purpose of this paper is to investigate how new energy (NE) stock markets of China interact and interrelate with each other and what the effect of large external shocks is on their connectedness from December 31, 2013, to November 8, 2022. Design/methodology/approach A DCC model is used to estimate the dynamic dependence among the NE stock markets. The spillover index technique (including both VAR and TVP-VAR models) is further introduced to test the causal effect. Findings The results highlight strong market connectedness in general for China's NE stocks. Specifically, the wind (geothermal) energy market tends to contribute more (less), featuring a stronger (weaker) association with other markets and a key role in information transmission (reception). Unexpected events, such as the Sino–US trade conflict and COVID-19, also significantly affect the level of market connections. Originality/value This paper takes an initial attempt to provide a clear-cut investigation about market connectedness among the NE stock markets of China via sectoral index data and the DCC model incorporating a break test as well as the spillover index method, which tests both return and volatility spillovers. This thus presents unprecedented evidence which has important implications for researchers, portfolio managers and policymakers.