THE EUA-CER SPREAD - COMPLIANCE STRATEGIES AND ARBITRAGE IN THE EUROPEAN CARBON MARKET Emilie Alberola, Caisse des Dépôts (Mission climat), +33 1 5850 4176, email@example.com Julien Chevallier, Imperial College London (Grantham Institute), +44 (0)20 7594 5796, firstname.lastname@example.org Morgan Hervé-Mignucci, Caisse des Dépôts (Mission climat) / Université Paris-Dauphine (CGEMP), +33 1 5850 9977, email@example.com Maria Mansanet-Bataller, Caisse des Dépôts (Mission climat), +33 1 5850 8522, firstname.lastname@example.org Overview The European Union Emission Trading Scheme (EU ETS) is the largest carbon market to date. It has been created to facilitate European countries’ compliance with the Kyoto protocol. The EU ETS shifts a large part of this Kyoto burden to its fixed sources of carbon emissions in a cap-and-trade scheme. Still, in order to provide these installations with more flexibility in achieving their objectives, the EU ETS partially allows these installations to use credits from Kyoto protocol’s offset projects to claim compliance. Theoretically, there should exist a perfect fungibility between European Union Allowances (EUAs), the carbon asset for European installations, and Certified Emissions Reductions (CERs), the main Kyoto project asset from Clean Development Mechanism (CDM), since both can be restituted to claim compliance for a ton of CO2 emitted. Yet, there is a price spread between those two assets. The CER-EUA spread attracts an increasing attention among brokers, investors and operators on emissions markets, because they may benefit from ”free lunch” arbitrage opportunities simply by using discounted CDM credits for their compliance under the EU ETS. For instance, -3.00 means that the CER futures price is EUR 3 less than the EUA futures price. After their issuance by a UN body, CERs are risk-free carbon assets, so the price should be equal to EUAs. So why do we observe a spread? Because there are various idiosyncratic risks affecting the supply and demand of CERs/EUAs, common risk factors, as well as other potential influences, which we propose to study in details in this article. The goal of this article is to identify how much of the CER-EUA spread may be explained through a careful statistical analysis using multivariate OLS regressions with dummy variables, and GARCH modelling as robustness checks. To date, this paper is the first attempt to empirically explain the CER-EUA spread. Methods There are numerous uncertainties arising around the delivery of primary CERs, including a wide range of validation, monitoring and issuance procedures. After issuance, spot market CERs (secondary CERs) should have the same low risk profile as EUAs. CER prices are determined on the supply side by the decisions of the CDM Executive Board which decides on the delivery rules, and on the demand-side by the decisions of the European Commission which determines the institutional fungibility within the European system. One also need to take into account the fact that CERs demand may also come from governements directly meeting their compliance within the Kyoto Protocol such as Japan, and thus which absorbs part of the CER demand away from compliance within the EU ETS. Yet, various risk factors impact the delivery of CDM credits and their importation within the European system, which may explain at least theoretically the existence of such premium. The importation of CERs within the EU ETS has been strictly limited to 1.4Gton of CO2 by 2012, with country-specific imports thresholds. This figure is computed by assuming an 13.4% limitation on CERs imports within the EU ETS on average. The CER-EUA spread is sensitive to the uncertainty affecting the supply and demand on both emissions markets. Its evolution depends on a wide range of institutional factors that we aim at statistically identifying in this article. This article aims at testing empirically the instrumental variables that have statistical explanatory powers concerning the variation of the CER-EUA spread overtime. First, we proceed by identifying first the risk premia specific to each emissions market. We specifically test fundamental carbon market drivers (energy, meteorological data, growth data, etc.) for explanatory power with EUA prices, secondary CER prices and finally with the EUA-CER spread. The intuition is that carbon market drivers might influence EUA and CER prices not to the same degree so that this difference of impact would be reflected in the price spread. Second, over the study period of two years, we created a database of spread-related official announcements (from the UNFCCC, the EC, market places with CER futures, etc.) that we expected would impact the CER-EUA spread. Third, we hypothetize that financial players and European utilities trading desks focus on the EUA-CER spread for speculative purposes. We will whether a set of speculative indicators have any explanatory power on the EUA-CER spread. We expect that (1) the differentiated impact of fundamental drivers on CERs and EUAs, (2) spread-specific announcements and (3) speculation would help explain the evolution of the spread between March 2007 and March 2009. Results Our results may be summarized as follows. First, we review the price development of the CER-EUA spread. Second, we detail the risk factors specific to CERs. Third, we evaluate the risk factors specific to the European carbon market. Fourth, we discuss the risk factors specific to both emissions markets. Fifth, our econometric analysis reveals the statistical significance of explanatory variables related to: forecast errors in CER supply from the UNEP/Risoe pipeline; technological and methodological changes representing institutional risk embedded within the validation of CDM projects; communications of the European Commission concerning changes in the import limit of CERs; the information relative to the transition between Phases II and III of the EU ETS concerning the import of CERs; the official information between the CDM Executive Board and the European Commision relative to the connection of the International Transaction Logs-Community Independent Transaction Log registries; communications in the COP meetings relative to the role of CDM in a post-Kyoto agreement. Conclusions Collectively, these results inform us on the explanatory power of changes in the CER-EUA spread, and simultaneously in the various risk factors that affect both emissions markets. References Alberola, E. and Chevallier, J. 2009. “European carbon prices and banking restrictions: Evidence from Phase I (2005-2007)”, The Energy Journal 30(3), 107-136. Capoor, K. and Ambrosi, P., 2008. “State and Trends of the Carbon Market 2008”, World Bank Institute, Research Report. IETA, 2008. “State of the CDM 2008: Facilitating a Smooth Transition into a Mature Environmental Financing Mechanism”, International Emissions Trading Association, Report. Mansanet-Bataller, M. and Pardo, A. and Valor, E. 2007. “CO 2 Prices, Energy and Weather”, The Energy Journal 28(3), 73-92.