Modelling the Time Series Dynamics of Carbon Emission Markets

Abstract

Carbon emission markets, which are designed to reduce emissions of global greenhouse gases (GHGs), have experienced rapid ongoing development even during the recent recession and have attracted considerable attention from policy makers and investors. Therefore, it is important to understand the time series dynamics of carbon asset prices and the behaviour of trading activities in carbon emission markets. This thesis, using the second commitment period data of the European Union emission trading scheme (EU ETS), examines the underlying dynamics driving carbon emission markets, including the performance of state dependent hedge ratios, the impact of arbitrage opportunities on feedback trading activities, as well as the influence of carbon allowance submission deadlines on the relationship between carbon spot and futures markets.
The research models the relationship between carbon spot and futures markets by incorporating state dependent characteristics into the return and volatility processes, and finds that the class of regime switching hedging strategies, particularly the proposed new framework which combines regime switching behaviour and disequilibrium adjustment in the mean with state dependent dynamic volatility process, significantly outperform competing methods for all the measures considered, and for both in-sample and out-of-sample analysis. The results indicate that risk managers using Markov regime switching models to hedge the risk in carbon markets achieve greater variance reduction and better hedging performance. Secondly, this study extends Sentana and Wadhwani’s (1992) feedback trading model by allowing arbitrage opportunities to affect the demand of feedback traders in carbon markets. The results suggest that there is no evidence of feedback trading in the carbon market, where institutional investors dominate, although the effect persists in a few other energy markets. This finding supports the view that institutional investors are not necessarily all feedback traders. Thirdly, when examining the influence of the carbon allowance submission deadline on the time series dynamics of carbon spot and futures markets, it is found that the equilibrium level, mean-reverting speed and no-arbitrage boundaries are affected by the submission deadline. However, the submission of allowances does not change the price discovery process of carbon emission markets, where this thesis finds that both the spot and futures markets Granger-cause each other. Furthermore, there is evidence that the volatility spillover process is different before and after the submission deadline, particularly from the spot market to the futures market. Therefore, in modelling the relationship between carbon spot and futures prices, the difference in the mean-reverting process of futures mispricing before and after the submission deadline should be accounted for. Overall, the thesis finds that the carbon emission markets yield different time series characteristics and trading behaviours from other financial markets. The findings of this thesis are of interest to risk managers, investors and arbitragers operating in the carbon emission market and could aid regulators in improving the mechanisms of the EU ETS in the next commitment period.