THE DRIVING RELATIONSHIP OF CHINA CARBON PRICE BASED ON DIFFERENT MARKET VOLATILITY STATES

Abstract

The China carbon market is a market-oriented designation for addressing climate issues. Price mechanism is the core of carbon market, studying on the price formation can promote the emission reduction targets. This article conducts an autoregressive adjusted Markov model to classify the carbon price state, and designs a multiple regression model to test the driving mechanism. The results show the second order autoregressive Markov model of MS(2)-AR(2) model can classify the carbon price into high and low volatility states. Furthermore, in high volatility state, carbon price is only significantly positively correlated with macroeconomic factors of China Securities Index 300 (CSI300) and European carbon price of European emission allowance future contract (EUAF), while in low volatility state, carbon price is significantly positively influenced by energy market products JM future (JMF) and Oil, macroeconomic factor of CSI300, and European carbon price of EUAF. Furthermore, the impact strength is weaker than the whole sample regression results. The results provide reference for investors to judge carbon price and reveal price trends.