تجزیه و تحلیل بهره وری بازار معاملات آتی گاز دی اکسید کربن اروپایی

The European Union Emissions Trading System (EU ETS) is the main international carbon trading market, in which European Union CO2 allowances (EUAs) are traded with increasing intensity. In order to help the market participants mitigate the market price risk, one possible way is to analyze the time range of market efficiency and the price discovery mechanism of EUA futures market and spot market. For this purpose, the paper provides the unit root test and the cointegration test for the EUA futures market during 2009–2011. Our result shows that the EUA futures market is efficient within 1 month. Furthermore, it illustrates that the impact of the price will continue for 3 months, examined by a vector error correction model (VECM).

After the commencement of the Kyoto Protocol in 2005, there has been an explosive growth in the global carbon trading market. The value of the global carbon trading market reached 40 billion euros in 2007, increased by 81.8% of the value in 2006, which was 22 billion euros. The market value for the first half of 2008 even reached the level for the whole year of 2007. The United Nations and the World Bank predict that the annual size of this market would be up to $ 60 billion in the period of 2008–2012, and the market capacity would be $ 150 billion, expecting to replace the oil market as the world’s largest market. The EU emissions trading system (EU ETS) is the major international carbon trading market, accounting for the 85.93% and 96.46% of the trading volume and turnover in the international carbon market. Unlike other markets, emerging carbon market faces greater market price risk in parallel of its rapid development, since it was not only effected by the market mechanism, but also under the impact of the instable exogenous environment, such as national politics (the climate negotiations), the temperature, the financial crisis and other special events. This paper outlines the time range of the EU ETS market efficiency by unit root test and cointegration test and then make forecast of the futures and spot prices by vector error correction model to help market participants mitigate the market price risk.

Throughthe analysis above,we can get the following conclusions: (1) The logarithms of spot and futures prices in EU ETS carbon futures market are non-stationary, whereas their first order differences are stable. This indicate that although it’s hard to control the long-term variation, the long-term equilibrium relationship may exist between them, which is confirmed by the following analysis and modeling. (2) The EU ETS carbon futures market is efficient in one month with a price discovery function of futures prices and can accurately predict the spot price. Therefore, the market participants can hedge the risk of spot trading price by using one month futures. (3) The optimal lag duration of VAR model established is 3. This shows that in the efficient range, the effect of EU ETS carbon futures market at special moment will last 3 terms, namely 3 months. Consequently, when using EU ETS carbon futures market to hedge risks, should not only operate within a limited range, but also pay close attention to the prices variation in three months. (4) The cointegration relationship between the two variables has been found through Johansen test on two price logarithm series. This shows that the indicators of futures market price which seems no rules to follow exist variety of long-term equilibrium relationship, which is useful to grasp the intrinsic characteristics of the market and take full advantages of the market. (5) The inadequacy of this article is that because the carbon futures market is the emerging market, and it aims to use economic measures to control the allocation and transference of carbon dioxide emission permits units in Europe. So, the categories of the current futures contracts are limited, leading to a smaller sample of this study and a lower credibility of analysis. We hope this problem can be solved by increasing the categories of futures contracts and accordingly increasing the number of samples.