Volatility Spillover Between the Carbon Market and Traditional Energy Market Using the DGC-t-MSV Model

This study employed the dynamic conditional correlation algorithm and incorporated the temporal dynamics of spillover effect to enhance the Multivariate Stochastic Volatility (MSV) model. Consequently, a DGC-t-MSV model (multiple stochastic volatility model of dynamic correlation coefficient with Granger causality test) was constructed to simulate and examine the volatility spillover effects between China's carbon market and the traditional energy market. The findings reveal the following: (1) A significant spillover effect in price volatility exists between China's carbon and traditional energy markets, with a notably fluctuating spillover index. The traditional energy market in China exerts a stronger unidirectional volatility spillover effect on the carbon market. Price fluctuations in the traditional energy market impact carbon market prices through mechanisms such as cost transmission and market expectations. (2) In the initial stages, the dynamic correlation between China's carbon and traditional energy markets showed an overall downward trend, underscoring the positive influence of policy incentives and technological advancements on the growth of alternative energy. A mutual weakening effect exists between the carbon and traditional energy markets. (3) Price fluctuations in China's carbon and traditional energy markets display a high degree of interdependence and short-term persistence, with evidence of a long memory and significant inertia in these price movements. Integration of the DGC-t-MSV model with the Bayesian approach and the Markov Chain Monte Carlo (MCMC) method and the introduction of a time-varying factor enabled the efficient measurement of the volatility spillover effect between China's carbon and traditional energy markets.