Research On Co-movement Of Information Conduction In And Out Of Carbon Markets

Climatic deterioration of environmental problems has drawn attention around the world. In order to achieve the Kyoto Protocol’s emission reduction targets,and to regulate and control emission through the market mechanism, the European Union has established European Union Emission Trading System(EU ETS) as the world’s largest permit market and launched carbon emissions allowances market and derivative markets. China also has established regional carbon market pilots.Carbon markets can be regarded as financial markets. The markets’ information can be conducted in the market, between the sub-markets and from external markets and be presented on prices as prices volatility. When the information conduction is frequent, the prices volatility will be violent to lead to price risks.In qualitative analysis, this thesis integrates current situation of domestic and foreign carbon markets, introduces the basic constitution, developmental progress, transaction performance. Then, it focuses on Chinese carbon market pilots to support the following chapters’ analyses. The results show that the carbon prices are prospective prices, historical prices volatility circumstance can be used to forecast future prices volatility.In quantitative analysis, firstly, this thesis studies the co-movement between the sub-markets from the perspective of information conduction. Based on the empirical study in European allowance spot prices, it analyzes the co-movement of the prices volatility between the sub-markets and builds the Vector Auto-regression(VAR) models to analyze the impulse response functions sets. The results show that the co-movement exists between sub-markets. Besides the relationship of supply and demand, the participants could forecast the price volatility. The information conduction is presented in the markets.Secondly, this thesis considers the co-movement between the carbon sub-markets and financial markets based on the information conduction. Because futures prices are widely used to study the price volatility co-movement in financial researches, the EUA futures prices is chosen as the empirical study, and is tested 19 time series from financial futures markets based on the ergodicity test in Granger causality test for 12 lag-lengths. Then, it builds the integrated Auto Regressive Moving Average and Generalized Auto-Regressive Conditional Heteroskedasticity(ARMA(1,1)- CGARCH) model to reflect the risk spillover in the condition of the long and short volatility from the perspectives of extreme risks and regular risks. The results show that the co-movement exists between sub-market and financial markets under different conditions.Then, this thesis firstly studies the price volatility co-movement in Chinese regional pilots. SZA is chosen to compare 5 pilots and 9 financial markets time series in the empirical study to analyze the risk spillover in the condition of the long and short volatility from the perspectives of extreme risks and regular risks. The results show that the co-movement exists between sub-markets and between the sub-market and financial markets. Besides, the long volatility linkages between them are closer and stronger in extreme risks than the short volatility linkages in regular risks.Furthermore, this thesis examines the risk-return relationship from the perspective of information conduction for the carbon futures market during phases I, II and III of EU ETS. The risk factor is derived from the newly developed model of LSW and is integrated into a GARCH framework. This new specification is compared with several GARCH-M type models to analyze the risk-return relationship in the carbon futures market. The results show that the explanatory result of new LSW model is superior to other models with the EUA data. Some policy suggestions regarding market efficiency are also provided.At last, this thesis builds a heterogeneous multi-agent model based on the NetLogo software by using a BA scale-free network model to depict the social structure. Considering both random strategy and preference strategy, the spreading of carbon market risk in the network and the intervention patterns from government are simulated to study the influencing factors for the spreading and the optimal prevention and control strategy. The results indicate that the spreading speed depends on both network structure and individuals’ conformity. The optimal prevention and control policy mainly depends on the individuals’ conformity, the scope of intervention and so on.