Carbon Futures Market Research Articles

Extreme co-movements between CO2 emission allowances and commodity markets and their response to economic policy uncertainty

This study employs the generalized extreme value - autoregressive conditional Fréchet - tail quotient correlation coefficient (GEV-AcF-TQCC) analytical framework to investigate the extreme co-movements between the EU carbon futures market and the commodity futures market. Subsequently, it also examines the response of the dynamic tail quotient correlation coefficient (TQCC) values to economic policy uncertainty stemming from the US using the linear Granger causality test. The empirical results demonstrate that the tail risk indices for both upside and downside trends of the two futures markets experience changes most of the time and show drastic changes during extreme events. More importantly, before the outbreaks of the COVID-19 pandemic (from September 2019 to February 2020) and the Russia-Ukraine conflict (from May 2021 to February 2022), the dynamic TQCC values for the downside trends of the two futures markets remain at relatively high levels. Of note, when examining the dynamic TQCC values between GSCI_down and EUA_down, as well as between GSCI_down and EUA_up, it can be observed that these TQCC values rise to higher levels during periods of extreme volatility. However, they quickly decline as the GSCI futures market experiences significant fluctuations during its downside trend. This pattern indicates a tail risk spillover effect from the GSCI futures market to the EUA futures market. Further analysis using the linear Granger causality test reveals that economic policy uncertainty is a significant driver of the extreme co-movements between the EU carbon and the commodity futures markets in most cases, in addition to the extreme co-movements between the downside trend of the EU carbon futures market and the upside trend of the commodity futures market. The insights gained from this study can provide valuable guidance and enlightenment for policymakers, financial investors, and academic researchers in understanding the dynamics of the extreme relationship between the two markets under discussion, and the impacts of economic policy uncertainty on their extreme co-movements.

Equilibrium bifurcation and extreme risk in the EU carbon futures market

Considering the long-term memory and volatility clustering of the European Union (EU) Carbon Emission Allowances (EUA) futures returns, based on the economy–energy–environment system perspective and the assumption of investors' heterogeneity, this study proposes a joint modeling approach combining the fractionally integrated generalized autoregressive conditional heteroscedasticity model (FIGARCH) and the stochastic cusp catastrophe model (SCC) to examine the equilibrium bifurcations and extreme risks in the EU carbon futures market. The relevant results are threefold. (1) The SCC model has good fitting effect and interpretability, and is an effective method for investigating catastrophe reactions under time-varying volatility conditions. (2) In the EUA futures market, chartists are mainly affected by short-term price and trading volume changes, which leads to the emergence of equilibrium bifurcations, while fundamentalists make investment decisions based on the economy, the energy market, and market supply–demand, which affects the asymmetry of equilibrium bifurcations. (3) Using the catastrophe criterion (i.e., Cardan's discriminant of the equilibrium surface equation), we identify148 equilibrium bifurcation time points in the EUA futures market from December 3, 2009 to September 16, 2020, most of which are concentrated in two upward periods with an average scale of extreme risks is about 32.51 %. Our analysis provides theoretical support for regulatory authorities to stabilize the carbon futures market and build a collaborative extreme risk management framework covering energy and macroeconomics, also proposing suggestions for traders to effectively prevent extreme risks.

Are economic policy uncertainty and carbon futures price interacting? Evidence from the European Union

This paper investigates the dynamic interplay between economic policy uncertainty and the carbon futures market within the context of global low-carbon development. The study utilizes a comprehensive dataset spanning 2005 to 2023, including daily observations of economic policy uncertainty (EPU) and carbon future prices (EUAP) in the European Union. Bootstrap subsample rolling window Granger causality tests are employed to examine the interrelationship between EPU and EUAP, providing robust and time-varying causal insights. The findings reveal the adverse impact of EPU on EUAP, highlighting that the volatility associated with economic policy uncertainty can serve as a predictive factor for carbon future prices. On the other hand, the EUAP exhibits a negative influence on the uncertainty of economic policy, indicating that the economic situation in Europe can be observed through the carbon future market. The findings presented in this study are in line with the underlying theoretical model of policy uncertainty and future prices. Considering the complex economic environment and the influence exerted by COVID-19, exploring the link between EPU and EUAP is crucial for informing investors’ decision-making and guiding the development of policy to enhance carbon market efficiency and promote a low-carbon economy.

Re-examining the efficiency of the EU carbon futures market in phase Ⅱ: price discovery and intertemporal arbitrage

Introduction: Carbon futures market plays an important role in energy conservation and emission reduction of energy-intensive firms, and its efficiency is largely reflected by the dynamic relationship between carbon spot and futures prices. Even though the EU carbon futures market has undergone three phases, its efficiency in Phase Ⅱ still contains much controversy.Methods: Based on the cost-of-carry model, we apply linear and nonlinear Granger causality test, vector error correction model and threshold vector error correction model to re-examine the efficiency of the carbon futures market in the second phase of the European Union Emissions Trading System from the perspectives of price discovery and intertemporal arbitrage.Results: i) the EU carbon futures market has the function of price discovery by virtue of the broad scope of participants and the consequent huge liquidity, suggesting that the carbon futures price can predict the carbon spot price; ii) the coefficient requirement of the cost-of-carry model is satisfied and the relationship between the European Union Allowance (EUA) futures and spot prices is consistent with the cost-of-carry model, which indicates that the former is an unbiased estimator of the latter and an equilibrium relationship exists between the two prices so that the carbon futures market is efficient in the long run; iii) however, the carbon futures market shows inefficiency in the short run since it has an error correction function only when the basis is less than −0.07 and the carbon futures price indicates a remarkably slow adjustment to the long-run equilibrium when there is deviation, which can be ascribed to the global financial crisis as well as its aftermath in 2008.Discussion: In the context of global warming and carbon neutrality, the results of this paper are of great significance to emitters, arbitrageurs, hedgers and policymakers in emerging and young carbon markets.

The impact of the Bitcoin price on carbon neutrality: Evidence from futures markets

The Paris Agreement (COP21) has provoked a global carbon neutralization episode in recent years. The mining of Bitcoin has been criticized for its tremendous demand for electricity power, which may be contradictory to the carbon neutralization process. Therefore, we attempt to scrutinize the impact of Bitcoin futures price shocks on the carbon futures markets in this study. We investigate the Bitcoin futures price shock toward carbon futures markets in different regions. We demonstrate that this spillover effect of the Bitcoin price shock is strongest in the US carbon futures market whilst weakest in the New Zealand carbon futures market. The US carbon futures market absorbed a large proportion of the Bitcoin futures price shock because Bitcoin is priced in US dollars. Furthermore, we also unravel the fact that the effect of Bitcoin price shocks persists over a long period of time, normally persisting for 4 periods regarding all three carbon futures markets. Finally, our research sheds light on the connection between Bitcoin futures and carbon futures. The nexus of Bitcoin futures with carbon futures rests on the mining mechanism of the Bitcoin system, which has attracted enormous attention in academia.

Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention

The uniqueness of this investigation lies in empirically testing and proving the contagion spillover of Bitcoin attention to carbon futures. Specifically, several models are adopted to investigate the explanatory and predictive abilities of Bitcoin attention to carbon futures. The results can be generalized as follows. First, Bitcoin attention Granger causes the variation of carbon futures. Second, Bitcoin attention shows a negative impact on carbon futures and an addition, an invert U-shaped connection exists. Third, the Bitcoin attention-based models can beat the commonly used historical average benchmark during out-of-sample forecasting both in statistical and economic levels. Fourth, we complete robustness checks to certify that the contagion spillover from Bitcoin attention to the pricing of carbon futures does exist. Finally, we prove the linear and non-linear impacts from Bitcoin attention to realized volatility of carbon futures. All the results prove that Bitcoin attention is an important pricing factor for carbon futures market.

Carbon and safe-haven flows

<abstract> <p>This paper explores the role of European Union Allowances (EUAs) as a safe haven for a range of assets and analyses the effect of safe-haven flows on the European carbon futures market. In particular, we demonstrate that EUAs can be considered a refuge against fluctuations in corporate bonds, gold and volatility-related assets in periods of market turmoil. Furthermore, we have shown that extremely bearish and bullish movements in those assets for which the EUA acts as a safe haven induce excess volatility in carbon markets, higher carbon trading volume and larger than normal EUA bid-ask spreads. These findings support the idea that some traders, by considering carbon futures as a refuge asset, induce safe-haven flows into the carbon market. The presence of these flows provides additional insights into the financialisation of the European carbon futures market.</p> </abstract>

The inconvenience yield of carbon futures

Since 2009, the European Carbon Futures Market has been in a permanent contango situation that is characterised by systematic negative convenience yields that allow investors to exploit profitable arbitrage opportunities. The objective of this paper is to analyse the possible drivers of these negative convenience yields. Our empirical results indicate that although some carbon trading variables are behind this contango situation, the carbon inconvenience yield is better explained if other financial markets and variables are considered, suggesting a financialization of the European Carbon Futures Market.

The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase

Based on the prices selected from European Energy Exchange (EEX) from 2013 to 2018, we investigate the inter-correlation of carbon spot and futures markets. Specifically, we adopt the widely used DCC-GARCH model and VAR-BEKK-GARCH model to conduct a comprehensive analysis on the carbon market, i.e., the dynamic correlation and volatility spillover between carbon spot and carbon futures. Moreover, we develop a hedge strategy based on the VAR-BEKK-GARCH model and calculate the hedging effectiveness (HE) value to evaluate the strategy performance. The empirical results show that (i) during our sample period, carbon spot and futures markets are highly correlated, (ii) carbon spot overflows to the futures market and vice versa, and (iii) the HE value is equal to 0.9370, indicating a good performance for the hedging strategy. Then, we provide further discussion on the relationship between carbon spot and futures markets by replacing our dataset with the data of phase II. The results do not change our conclusions on the dynamic correlation and volatility spillover. However, the HE value of phase III is higher than that of phase II, which indicates that the carbon futures market of phase III is not only an available market to hedge risk from the contemporaneous carbon spot market but also has a better hedge effectiveness than phase II.

Multifractal detrended cross-correlation analysis of the relation between price and volume in European carbon futures markets

Recently, with the development of European carbon futures markets, the complex dynamic relationship between price and volume has become the focus of energy research area. In our research, we applied multifractal detrended cross-correlation analysis method (MF-DCCA) to investigate the cross-correlation and multifractality between price and volume in European carbon futures markets. Firstly, the analysis of basic statistics show that the European carbon futures market has obvious non-normal, peak-heavy-tailed distribution, which does not satisfy the normal distribution hypothesis in the efficient market. Secondly, through multifractal detrended cross-correlation analysis, we conclude that trading price and volume relationship in European carbon futures markets has a non-linear dependence. Thirdly, we find the existence of power-law cross-correlations between price and volume in European carbon futures markets. Finally, the relationship between price and volume is non-linear. After random rearrangement and phase treatment of correlation coefficients, the long-range correlation of small fluctuations and large fluctuations and the fat tail distribution of series are the reasons for the formation of multifractality.

Could Market Making be Profitable in The European Carbon Market?

We investigate when market making can be profitable in the European Carbon Futures market, by developing an order type selection rule, based solely on transaction level data. We employ a granular approach that uses an observable variable, i.e. trading intensity, to extract the liquidity and information price components and we investigate their impact on spreads, volatility and ultimately on the profitability of different order types. We find that market orders are always less profitable than limit orders. In addition, market makers are expected to derive most of their profits in a low trading intensity environment, mainly due to higher liquidity commissions and a lower probability of dealing with better informed agents. In contrast, an unconditional limit order submission strategy from an off-floor trader should not be preferred, apart from a medium trading intensity environment, where information and liquidity premia adequately compensate them for execution and information risk.

Could Market Making Be Profitable in the European Carbon Market?

We investigate when market making can be profitable in the European Carbon Futures market, by developing an order type selection rule, based solely on transaction level data. We employ a granular approach that uses an observable variable, i.e. trading intensity, to extract the liquidity and information price components and we investigate their impact on spreads, volatility and ultimately on the profitability of different order types. We find that market orders are always less profitable than limit orders. In addition, market makers are expected to derive most of their profits in a low trading intensity environment, mainly due to higher liquidity commissions and a lower probability of dealing with better informed agents. In contrast, an unconditional limit order submission strategy from an off-floor trader should not be preferred, apart from a medium trading intensity environment, where information and liquidity premia adequately compensate them for execution and information risk.

Do carbon traders behave as a herd?

This paper shows the existence of herding behavior in the European Carbon Futures Market and studies its possible causes and consequences. This market is characterized by leading the carbon price discovery process and by being highly dominated by professional traders. Both features make it an appropriate environment for the existence of herding. A patterns analysis indicates that the herding level increases in speculative periods, on those days on which the price and size clustering effect is stronger, and with the arrival of carbon-related news. Regarding possible market drivers, we find that herding behavior is positively related with the number of trades, the intraday volatility and on days with extreme returns. Our results appear to support the claim that the lower the availability of information, the higher the level of herding. Finally, we show that herding increases market volatility and leads carbon traders to overreact.

Is information assimilated at announcements in the European carbon market?

We examine the high frequency new information impact on prices, volatility, trading volume and illiquidity at scheduled macroeconomic and verified emissions announcements for the European carbon futures market. Verified emissions, United States non-farm payroll and German new factory order macroeconomic announcements impact carbon prices swiftly, within 5min. We show that a one standard deviation surprise increase in verified emission announcements is associated with an approximate ten percentage point (9.96%) increase in carbon futures returns. A wait-and-see stylized trading behavior is evident at announcements in volatility and trading volumes. Market illiquidity increases at announcements in relation to United States non-farm payroll, albeit there is no evidence of an increase in illiquidity prior to announcements. The development of new information impact, over time, occurs mainly in the at-announcement 5-minute time interval.

Interval Forecasting of Carbon Futures Prices Using a Novel Hybrid Approach with Exogenous Variables

This paper examines the interval forecasting of carbon futures prices in one of the most important carbon futures market. Specifically, the purpose of this study is to present a novel hybrid approach, which is composed of multioutput support vector regression (MSVR) and particle swarm optimization (PSO), in the task of forecasting the highest and lowest prices of carbon futures on the next trading day. Furthermore, we set out to investigate if considering some potential predictors, which have strong influence on carbon futures prices, in modeling process is useful for achieving better prediction performance. Aiming at testing its effectiveness, we benchmark the forecasting performance of our approach against four competitors. The daily interval prices of carbon futures contracts traded in the Intercontinental Futures Exchange from August 12, 2010, to November 13, 2014, are used as the experiment dataset. The statistical significance of the interval forecasts is examined. The proposed hybrid approach is found to demonstrate the higher forecasting performance relative to all other competitors. Our application offers practitioners a promising set of results with interval forecasting in carbon futures market.

Is Information Assimilated at Announcements in the European Carbon Market?

We examine the high frequency new information impact on prices, volatility, trading volume and illiquidity at scheduled macroeconomic and verified emissions announcements for the European carbon futures market. Verified emissions, United States non-farm payroll and German new factory order macroeconomic announcements impact carbon prices swiftly, within 5 minutes. We show that a one standard deviation surprise increase in verified emission announcements is associated with an approximate ten percentage point (9.96%) increase in carbon futures returns. A wait-and-see stylized trading behavior is evident at announcements in volatility and trading volumes. Market illiquidity increases at announcements in relation to United States non-farm payroll, albeit there is no evidence of an increase in illiquidity prior to announcements. The development of new information impact, over time, occurs mainly in the at-announcement 5-minute time interval.

The Return and Volatility Spillover between Carbon Futures Market and Global Financial, Energy and Commodity Futures Markets

Financialization of carbon market and global economy have made the fluctuation of carbon emission allowance prices vulnerable to international shocks and risk management become more and more complicated for both investors and fossil fuel consumption enterprises. Based on studying the ergodicity of the Granger causality test for different lag-lengths, this paper investigates the return and volatility transmission between carbon futures price and a data set of 19 financial, energy and commodity time series results show that there exists several causal relationships between carbon futures market and financial, energy and commodity futures markets. The connections between carbon futures market and financial markets are especially strong. Despite that spillovers in different phases are different, volatility linkage between carbon futures markets and these markets is closer and stronger than the return linkage in general. Moreover, extreme returns and risks also have significant leading impacts on regular returns and risks.

Liquidity and resolution of uncertainty in the European carbon futures market

We investigate whether liquidity introduces or helps resolve uncertainty in Phase I and the first year of Phase II of the European carbon futures market. We propose a distinction between ‘absolute’ or overall liquidity and that which is ‘relative’ to a benchmark. For this purpose, we suggest volume-weighted duration as a natural measure of trading intensity as a proxy for liquidity, and we model it as a rescaled temporal point process. The new model is called Autoregressive Conditional Weighted Duration (ACWD) and is shown to outperform its discrete modelling counterparts. Liquidity is found to play a dual role, with higher relative liquidity introducing uncertainty and higher absolute liquidity accelerating uncertainty resolution, thus, enhancing market efficiency.

What makes carbon traders cluster their orders?

The ability to trade large amounts of assets at low costs could be hindered when the size of the orders is concentrated at specific trade sizes. This paper documents evidence of size clustering behavior in the European Carbon Futures Market and analyzes the circumstances under which it happens. Our findings show that carbon trades are concentrated in sizes of one to five contracts and in multiples of five. We have also demonstrated that more clustered prices have more clustered sizes, suggesting that price and size resolution in the European Carbon Market are complementary and that carbon traders round both the price and the size of their orders. Finally, the analysis of the key determinants of the size clustering reveals that traders use a reduced number of different trade sizes when uncertainty is high, market liquidity is poor, and the desire to open new positions and cancel old ones is very strong.

Trading patterns in the European carbon market: The role of trading intensity and OTC transactions

This paper examines the effect of trading intensity and OTC transactions on expected market conditions in the early development period of the European Carbon futures market. Past duration and trading intensity are used as information related order flow variables in modelling time between transactions in two new specifications of Autocorrelation Conditional Duration (ACD) models. This allows for specific investigation of non-linear asymmetric effects on expected duration and the impact of OTC transactions. Evidence is presented of two main types of trading episodes of increased and decreased trading intensity. Both have a significant impact on price volatility, which increases further if an OTC transaction intrudes. OTC transactions also play a dual role. They slow down trading activity in the short term (over the next five transactions) but increase it substantially in the long term (over ten transactions). Both the liquidity and information price impact components increase following an OTC trade, but the information impact is greater. Price volatility calms down faster than liquidity effects following an OTC trade, and this is more pronounced in ECX and in Phase II. The combined evidence points towards increased market depth, efficiency and maturity of the trading environment.