Speculation Investigation from Microcosmic Traders Behaviors and Its Effects on Carbon

Speculation Investigation from Microcosmic Traders Behaviors and Its Effects on Carbon Price in EU-ETS

[Yinpeng Liu, Center for Energy & Environmental Policy research, Institute of Policy and Management, Chinese Academy of Sciences, Beijing, China, CA, 86-010-59358826,

[Jianfeng Guo, Center for Energy & Environmental Policy research, Institute of Policy and Management, Chinese Academy of Sciences, Beijing, China, CA, 86-010-59358826,

Overview

Emissions trading system (ETS) is one of the most important policy tools to reduce greenhouse gas emissions. By far, the European Union emissions trading system (EU-ETS) is the biggest carbon market in worldwide. As a valuable practice sample of ETS, study on factors which affect carbon price has become increasingly hot research field. Some research shows that framework and rules of EU-ETS have an impact on carbon price; some studies focus on external factors, such as price of energy market, weather, low-carbon technology diffusion; some researcher revealed that the carbon price is also affected by macroeconomic conditions. Fewer studies took speculation as a factor, but none of them investigate speculation signal from microcosmic trader activities level. In this paper, speculation features was acquired by analyzing traders attributes and trading pattern with comprehensive transaction log dataset, and then, we examined its impact on carbon price in first period of EU-ETS.

Methods

First, using the complete first period European Union Transaction Log (EUTL) data, we identified the non-commercial speculative transaction by analysing the profiles of traders and microcosmic transaction pattern within EU-ETS, then a new index for net long position of this non-commercial transaction could be extracted accurately. Second, to portray the activity level of traders, we calculated daily trading volume and circulating volume in EU-ETS by tracing allowance flow, and then made an index using the ratio of these two values. Finally, taking net non-commercial long position as speculation index, meanwhile, including indexes reflexing market activity, macroeconomic conditions and fossil energy price, we constructed an DCC-GARCH model to study how the speculation impact carbon price interactively, as well the features of these impacts around different policy implementation periods.

Results

First, the empirical results suggest that macroeconomic conditions and fossil energy price can significantly influence carbon price, where the former factor exerts a positive impact, while the latter impact carbon price negatively; Second, in the whole time, market activity has no significant impact on carbon price, but we found that, given different market activity and carbon price, these factors especially speculation play varies roles in EU-ETS. Third, in general, speculation sharply intensified the volatility of carbon price.

Conclusions

Based on the whole transaction log of first period EU-ETS, we identified the profile and transaction pattern of traders to capture their speculative actions accurately, and construct index of speculation and market activity. These two indices come from closed transaction data can be more convictively to explain the speculation behaviour in the market. In the first period, EU-ETS exist a large number of speculators, not only the personal holding accounts, but also some speculative behaviours appeared on operator holding account though whose emitting installation was regulated by EU-ETS. The commercial trading of operator holders happened mostly near the time when the allowance was allocated or surrendered because they must have enough allowance for emission, but the non-commercial trading was active during the whole period. The empirical analyses demonstrate that, plenty of speculation transactions are a really strong force to intensify the volatility of carbon price.

References

[1].Jan Horst Keppler, Maria Mansanet-Bataller,2010. Causalities between CO2, electricity, and other energy variables during phase I and phase II of the EU ETS. Energy Policy, 38(2010) 3329-3341

[2].Maria Mansanet-Bataller, Julien Chevallier, Morgan Herve-Mignucci, Emilie Alberola, 2011. EUA and sCER phase II price drivers: Unveiling the reasons for the existence of the EUA-sCER spread. Energy Policy, 39(2011) 1059-1069

[3].Frank J. Convery and Luke Redmond,2007. Market and Price Developments in the European Union Emissions Trading Scheme. Review of Environmental Economics and Policy, 1(2007) 88-111

[4].Erik D. Delarue and William D. D'haeseleer, 2007. Price determination of ETS allowances through the switching level of coal and gas in the power sector. International Journal of Energy Research, 31,1001-1015

[5].Timothy J. Considine, 2000. The impacts of weather variations on energy demand and carbon emissions. Resource and Energy Economics, 22, 295-314

[6].Eva Benz, Stefan Truck, 2009. Modeling the price dynamics of CO2 emission allowances. Energy Economics, 31,4-15

[7].A. C. Christiansen, A. Arvanitakis, K. Tangen & H. 2009. Hasselknippe, Price determinants in the EU emissions trading scheme. Climate Policy,5,15-30