In this paper, we analyse the dynamic relationship among the Chinese renewable energy stock prices, the US renewable energy stock prices, oil prices and technology stock prices. We apply a four-variable lag-augmented vector autoregressive (LA-VAR) model to study the return interactions among the variables.
Moreover, we also use generalised autoregressive conditional heteroskedasticity (GARCH) models to study the dynamic conditional volatility of the Chinese renewable energy stock prices. The empirical results indicate that both return and conditional volatility of the Chinese renewable energy stock prices can be explained by past movements of the US renewable energy stock prices and technology stock prices.
In addition, we find significant GARCH effects exist in the Chinese renewable energy stock prices. However, we only find weak statistical evidence to reveal the significance of the leverage effects in the market. (C) 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.