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Research on the Carbon Price Volatility with the Stochastic Volatility Model

Author: ZhangYuJuan
Tutor: HeChaoLin
School: Anhui University of Engineering
Course: Management Science and Engineering
Keywords: carbon emission stochastic volatility model leverageeffect Markov chain Monte method (MCMC) mean reversion
CLC: F831.5
Type: Master's thesis
Year: 2013
Downloads: 37
Quote: 0
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Abstract

With the continuous development of the international carbon trading market, more and more countries take part in the trading.In order to dominate the dominant position of carbon trading market, the right of pricing becomes the main issue among the countries.Compared with the international market, the carbon trading market in our country is in its infancy and many problems exits, such as:the trading price of Carbon emission rights is not reasonable and the trading Mechanism is not perfect. Our country plays the role of cheap CER exporters and without the pricing right although it occupies a large share of the CDM market. However, in order to achieve a low-carbon economy, we must exert the function of carbon market pricing and the price should reflect the scarcity of carbon emissions fully. Needless to say, pricing of carbon emissions become the key problem during the development. According to the theory of financial markets, a price returns to its long-term equilibrium price is inevitable in a mature financial market. So, beginning from the study the fluctuation rules of carbon emission rights price, this paper analyzes the price of carbon trading in-depth, carries on the empirical research to give an insight into the variation rule of international carbon emissions price variation rule and puts forward related policy suggestions based on the successful experience of international carbon trading market operation to perfect carbon emissions trading system of the domestic market by combining with the characteristics of the carbon trading market in China.Firstly, based on the characteristics of carbon emission rights such as virtual sex, interests, policies and price volatility, from the perspective of financial markets we analysis the impact factors of the pricing of carbon emissions:the first market is mainly for emission reduction targets, emission reduction technology and management costs as well as market risk; the second market is mainly for energy prices and the level of predicting the price. In addition, a detailed analysis about the stylized facts of the volatility with the price of carbon emission rights is available. Then, on the basis of the standard stochastic volatility model, a Bayesian analysis which based on regime switching stochastic volatility model is used for estimating the MCMC parameter and analyzing the EU carbon emissions trading market price fluctuations Empirical analysis.The results show that, due to the limitations of the effectiveness of the market, international carbon market does not have the characteristics of mean reversion in the short term. However, with the constant improvement of the international policies and market mechanisms, it is inevitable that international carbon market price to return to its long-term equilibrium price. Finally, in order to improve the pricing power of our country in the international carbon emissions trading market position. We give some suggestions from the value method of valuation of futures market with carbon emission rights, carbon emissions, carbon trading, risk management system and carbon financial derivatives.Main innovations of this paper lie in:1. Research methods. At present, although the research on the carbon trading market price has already begun, most research achievements are still in the qualitative research phase from the view of the existing research results published. This paper empirically researches price data of the EU carbon emissions trading market after analyzing the volatility features of carbon emissions trading price based on the assets stochastic volatility model, further refines the volatility characteristics of the carbon emissions price.2. The method of estimating the parameters of the model.Estimating the latent variable model parameters has been the focus of academic research, this paper uses the MCMC method to estimate the latent variable model parameters to solve the hidden variable filtering and prediction problems effectively.

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