Accounting for Carbon Emission Allowances in the European Union: In Search of Consistency

Abstract

With the commencement of Phase III of the European Union Emissions Trading System (EU ETS) in 2013, it is projected that approximately one-half of emission allowances will be acquired through auctioning and the provision of free allocations to installations will be substantially tightened. As a result, it is likely that many companies will hold purchased (as opposed to freely allocated or gratis) allowances and will have more significant liabilities under the scheme. The accounting treatment of emission allowances has therefore become more relevant and the lack of uniformity in practice that resulted after the withdrawal of IFRIC 3 is now a more pressing concern. This study uses content analysis to examine disclosed accounting policies of companies with significant emission liabilities under the EU ETS and identifies three more common approaches adopted to date. These can be generally described as the following: (i) a net liability approach, based on the classification of allowances as intangibles but only showing an emission liability when it exceeds the free allocation; (ii) an approach broadly based on IFRIC 3 (recognising the free allocation at fair value and a corresponding gross liability under the EU ETS); and (iii) an approach based on inventory classification, with free allocations given at nil value. The diversity in these treatments highlights the need for guidance from the International Accounting Standards Board.     

The ‘Cost’ of Climate Change: How Carbon Emissions Allowances are Accounted for Amongst European Union Companies

Following the withdrawal of IFRIC 3: Emissions Rights in 2005, European Union (EU) companies participating in an Emissions Trading Scheme (ETS) do not have definitive guidelines as to how to account for carbon emissions allowances. Using a content analysis methodology, this study examines the disclosed accounting policies of companies participating in the EU ETS, and reveals how, in the absence of clear guidance, they account for their carbon emissions allowances. As the accounting method adopted will impact upon a company's financial statements, these findings are of interest to accounting standards setters, investors, financial reporting preparers, auditors, and researchers.     

Detecting and modelling the jump risk of CO2 emission allowances and their impact on the valuation of option on futures contracts

Modelling CO₂ emission allowance prices is important for pricing CO₂ emission allowance linked assets in the emissions trading scheme (ETS). Some statistical properties of CO₂ emission allowance prices have been discovered in the literature ignoring price jumps. By employing real data from the ETS, this research first detects the jump risk using a jump test and then verifies jump effects in modelling CO₂ emission allowance prices by comparing the in-sample and out-of-sample model performance. We suggest a model which can capture the statistical properties of autocorrelation, volatility clustering and jump effects is more appropriate for modelling CO₂ emission allowance prices. We establish a general framework for pricing CO₂ emission allowance options on futures contracts with these properties and find that the jump risk significantly affects the value of the CO₂ emission allowance option on futures contracts. More importantly, we demonstrate that the dynamic jump ARMA–GARCH model can provide more accurate valuations of the CO₂ emission allowance options on futures than other models in terms of pricing error.     

The European Emissions Trading Scheme: An exploratory study of how companies learn to account for carbon

European companies were confronted with new organisational challenges when the European Emissions Trading Scheme (EU ETS) was introduced in 2005. What were their cognitive sources for developing an orientation in this scheme? This paper presents original data from a survey of the University of Hamburg, dealing with companies’ responses to the EU ETS in 2005–2007. The survey was conducted three times and addressed all companies covered by the trading scheme in Germany, the United Kingdom, Denmark and the Netherlands (response rate of 19%–23% over three years). Results are provided on the share of companies that traded emission allowances, on the knowledge of their own CO₂ abatement costs, on the organisational unit that was responsible for decisions on emissions trading, and on the use of internal and external sources of advice. The data thus provides an insight into the cognitive resources that companies brought to bear when looking for an orientation in the new trading scheme. The sources of advice and the internal assignment of responsibility build the framework of competencies in which companies learn to account for carbon.     

On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting

This article documents the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European climate exchange (ECX), which is valid under the EU emissions trading scheme (EU ETS). Realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-normals hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi in J Financ Econ 7:174–196, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability.     

Futures Options and the Volatility of Futures Prices

Assuming nonstochastic interest rates, European futures options are shown to be European options written on a particular asset referred to as a futures bond. Consequently, standard option pricing results may be invoked and standard option pricing techniques may be employed in the case of European futures options. Additional arbitrage restrictions on American futures options are derived. The efficiency of a number of futures option markets is examined. Assuming that at-the-money American futures options are priced accurately by Black's European futures option pricing model, the relationship between market participants' ex ante assessment of futures price volatility and the term to maturity of the underlying futures contract is also investigated empirically.     

Noise, equity prices, and hedging: A new approach

The existence of noise trading in equity markets has possible economic implications for arbitrage, and asset pricing. In terms of pricing, noise trading can lead to excess volatility which has been shown to influence the value of options and futures. Furthermore, option research shows that modeling volatility leads to improved hedging performance. To this end, we derive a general hedging model for equity index futures in the presence of noise trading. Our analysis shows how the level and dynamics of noise trading should influence a hedger's behavior. Finally, we empirically test our model using the NASDAQ-100 index futures and FTSE 100 index futures over the period of January 1998 to May 2003.     

Modeling the relationship between European carbon permits and certified emission reductions

Recent years have seen an expansion of carbon markets around the world as various policymakers attempt to reduce CO2 emissions. This paper considers two of the major types of carbon permits: European Union Allowances (EUAs, arising from the European Union Emissions Trading Scheme, EU ETS) and certified emissions reductions (CERs, arising from agreements made under the Kyoto Protocol). The rules of the EU ETS allow for some use of CERs in place of EUAs by EU firms, but this substitutability is only partial. Allowing for carbon permits from different sources to substitute for one another should help achieve CO2 emissions reductions at least cost. Understanding the degree and nature of linkages (if any) between the markets for EUAs and CER is, thus, an important policy issue. In this paper, we jointly model the spot and future prices of an EUA along with the price of a CER using flexible multivariate time series methods which allow for time-variation in parameters. We find evidence of contemporaneous causality between these three variables with the EUA futures price playing the dominant role in driving this relationship. We also document time-variation in this relationship which is associated with macroeconomic events such as the financial crisis of late 2008 and early 2009. We find very little evidence of volatility spillovers or of Granger causality among any of the variables. We discuss how these empirical findings are consistent with markets which are loosely linked, but are not tightly linked as would be found for perfectly substitutable assets in efficient financial markets.     

Carbon Markets in China: Development and Challenges

China is attempting to initiate its own carbon market—an important market-based policy instrument which would determine the fate of global climate policy as the largest emitter of carbon dioxide across the world. This article looks at carbon trading development so far and examines the key challenges ahead in China. These past experiences—whatever from international CDM practice, or SO₂ emission trading and a domestic voluntary carbon market—have paved the solid way to build the existing ETS pilots similar to European Union Emissions Trading System (EU ETS). The investigation into China’s ETS pilots discovered some important and urgent issues such as the capsetting and deepening energy market reform.     

Commodity derivatives valuation with autoregressive and moving average components in the price dynamics

In this paper, we develop a continuous time factor model of commodity prices that allows for higher-order autoregressive and moving average components. We document the need for these components by analyzing the convenience yield’s time series dynamics. The model we propose is analytically tractable and allows us to derive closed-form pricing formulas for futures and options. Empirically, we estimate a parsimonious version of the general model for the crude oil futures market and demonstrate the model’s superior performance in pricing nearby futures contracts in- and out-of-sample. Most notably, the model substantially improves the pricing of long-horizon contracts with information from the short end of the futures curve.     

Investment shocks and the commodity basis spread

I identify a “slope” factor in the cross section of commodity futures returns: high-basis commodity futures have higher loadings on this factor than low-basis commodity futures. Combined with a level factor (an index of commodity futures), this slope factor explains most of the average excess returns of commodity futures portfolios sorted by basis. More importantly, I find that this factor is significantly correlated with investment shocks, which represent the technological progress in producing new capital. I investigate a competitive dynamic equilibrium model of commodity production to endogenize this correlation. The model reproduces the cross-sectional futures returns and many asset pricing tests.     

VIX option pricing and CBOE VIX Term Structure: A new methodology for volatility derivatives valuation

This study integrates CBOE VIX Term Structure and VIX futures to simplify VIX option pricing in multifactor models. Exponential and hump volatility functions with one- to three-factor models of the VIX evolution are used to examine their pricing for VIX options across strikes and maturities. The results show that using exponential volatility functions presents an effective choice as pricing models for VIX calls, whereas hump volatility functions provide efficient out-of-sample valuation for most VIX puts, in particular with deep in-the-money and deep out-of-the-money. Pricing errors for calls can be further reduced with a two-factor model.     

Common asset pricing factors in volatilities and returns in futures markets

Factor-based asset pricing models have been used to explain the common predictable variation in excess asset returns. This paper combines means with volatilities of returns in several futures markets to explain their common predictable variation. Using a latent variables methodology, tests do not reject a single factor model with a common time-varying factor loading. The single common factor accounts for up to 53% of the predictable variation in the volatilities and up to 14% of the predictable variation in the means. S&P500 futures volatility predicted by the factor model is highly correlated with volatility implied in S&P500 futures options. But both the factor and implied volatilities are significant in predicting future volatility. In derivatives pricing, both implied volatility from options and factors extracted from asset pricing models should be employed.     

Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis

This paper models the relationship of European Union Allowance spot- and futures-prices within the second commitment period of the European Union emissions trading scheme. Based on high-frequency data, we analyze the transmission of information in first and second conditional moments. To reveal long-run price discovery, we compute common factor weights of Schwarz and Szakmary (1994) and information shares of Hasbrouck (1995) based on estimated coefficients of a VECM. To analyze the short-run dynamics, we perform Granger-causality tests. We identify the futures market to be the leader of the long-run price discovery process, whereas the informational role of the futures market increases over time. In addition, we employ a version of the UECCC-GARCH model as introduced by Conrad and Karanasos (2010) to analyze the volatility transmission structure. The volatility analysis indicates a close relationship between the volatility dynamics of both markets, whereas in particular we observe spillovers from the futures to the spot market. As a whole the investigation reveals that the futures market incorporates information first and then transfers the information to the spot market.     

Does increased hedging lead to decreased price efficiency? The case of VIX ETPs and VIX futures

We examine the impact of the introduction of VIX exchange‐traded products (ETPs) on the information content and pricing efficiency of VIX futures. We document that trades in VIX futures have become less informative and that pricing errors exhibit more persistence after the introduction of VIX ETPs. In addition, we observe that the price process of the VIX futures has become noisier over time. These findings suggest that the introduction of the VIX ETPs had a prominent effect on the properties and dynamics of the VIX futures.     

Random sources correlations and carbon futures pricing

For a long time, the correlation between random sources has never been considered in carbon futures pricing, which virtually exists. We document the presence of high correlation between variations in convenience yields of carbon futures with different maturities, whose essence is correlation between random sources. Correlation of random sources arises from the long coverage of convenience yield of carbon emission spot and the complementarity in expiration between carbon futures with different maturities. Since if random sources are correlated will significantly affect the dynamics of convenience yield and finally affect futures prices, we introduce quantum field method to account for the impact of this correlation on futures prices, and proposes the correlation between random sources extended HJM convenience yield model (CRS-HJM-CYM). Empirical results indicate CRS-HJM-CYM performs better than traditional model owing to the role of correlation, which means the correlation between random sources is a pivotal factor in carbon futures pricing.     

Empirical performance of multifactor term structure models for pricing and hedging Eurodollar futures options

This article compares two one-factor, two two-factor, two three-factor models in the HJM class and Black's [Black, F. (1976). The pricing of commodity contracts. Journal of Financial Economics, 3, 167-179.] implied volatility function in terms of their pricing and hedging performance for Eurodollar futures options across strikes and maturities from 1 Jan 2000 to 31 Dec 2002. We find that three-factor models perform the best for 1-day and 1-week prediction, as well as for 5-day and 20-day hedging. The moneyness bias and the maturity bias appear for all models, but the three-factor models produce lower bias. Three-factor models also outperform other models in hedging, in particular for away-from-the-money and long-dated options. Making Black's volatility a square root or exponential function performs similar to one-factor HJM models in pricing, but not in hedging. Correctly specified and calibrated multifactor models are thus important and cannot be replaced by one-factor models in pricing or hedging interest rate contingent claims.     

The volatility of temperature and pricing of weather derivatives

We propose an Ornstein–Uhlenbeck process with seasonal volatility to model the time dynamics of daily average temperatures. The model is fitted to approximately 45 years of daily observations recorded in Stockholm, one of the European cities for which there is a trade in weather futures and options on the Chicago Mercantile Exchange. Explicit pricing dynamics for futures contracts written on the number of heating/cooling degree-days (so-called HDD/CDD futures) and the cumulative average daily temperature (so-called CAT futures) are calculated, along with a discussion on how to evaluate call and put options with these futures as underlying.     

碳排放权期货市场流动性特征分析及启示

碳排放权期货品种已成为世界期货市场研究和发展的重要战略品种。根据碳排放权期货市场的发展现状,本文选取欧洲气候交易所的交易品种作为研究对象,分阶段、分品种对其交易品种的流动性特征进行了分析。通过总结碳排放权市场流动性特征变化,得出碳排放权期货市场的发展经验,为今后我国碳排放权期货市场的建立奠定基础。     

Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence

This paper introduces a new method for measuring nonlinear predictability in financial price changes: the so-called intermittency coefficient, a parameter of the multifractal random walk model by Bacry et al. (2001). As the intermittency coefficient can quantify the degree of nonlinear deviation from a random walk, we employ its estimates from financial data as a proxy for the loss of financial market efficiency. In addition, we propose a new statistical test of the random walk hypothesis. In an empirical application using data from the largest currently existing market for tradable pollution permits, the European Union Emissions Trading Scheme (EU ETS), we show that the degree of efficiency of this market remains largely unchanged over the period of observation 2008–2019. This suggests that the market has reached a mature state: informational efficiency in Phase III remains at a level comparable to Phase II. What is more, the EU ETS is found to be more efficient than the US stock market. This result, surprising as such, is largely attributable to the lower exposure to global economic shocks of the EU ETS.