Showing papers on "Brent Crude published in 2014"
TL;DR: The authors examined the impacts of three types of OPEC news announcements on volatility spillovers and persistence in international energy and cereal commodity markets, and showed that the persistence of volatility decreases for the crude oil and heating oil (gasoline) returns after accounting for the OPEC announcements in these multivariate GARCH models.
214 citations
TL;DR: Sentiment is shown to influence both West Texas Intermediate (WTI) and Brent futures prices during the period 2002-2013 as mentioned in this paper, while controlling for stock indices, exchange rates, financial costs, inventory and supply levels as well as OPEC activity.
Abstract: Sentiment is shown to influence both West Texas Intermediate (WTI) and Brent futures prices during the period 2002-2013. This is demonstrated while controlling for stock indices, exchange rates, financial costs, inventory and supply levels as well as OPEC activity. Sentiment indices are developed for WTI and Brent crude oils using a suite of financial proxies similar to those used in equity research where the influence of sentiment has already been established. Given the novel nature of this study, multiple hypothesis testing techniques are used to ensure that these conclusions are statistically robust.
60 citations
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TL;DR: In this article, the authors explore the links between Brent crude oil index and stock markets index in OECD countries and estimate time-varying conditional correlation relationships among these variables by employing Engle's (2002) Dynamic Conditional Correlation (DCC) to detect eventual volatility spillovers, which are typically observed in stock markets and oil prices.
Abstract: This paper aims to explore the links between Brent crude oil index and stock markets index in OECD countries. We estimate time-varying conditional correlation relationships among these variables by employing Engle’s (2002) Dynamic Conditional Correlation (DCC). This process detects eventual volatility spillovers, which are typically observed in stock markets and oil prices. Our sample consists of monthly frequencies stock indexes and oil price, covering 10 OECD countries for the period of January1990- September 2012. Oil price shocks in periods of world turmoil and political events have an important impact on the relationship between oil and stock market prices.
38 citations
TL;DR: The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate and Brent crude oil spot prices.
Abstract: A new method based on integrating discrete wavelet transform and artificial neural networks (WANN) model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS). The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI) and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.
35 citations
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TL;DR: In this article, the authors investigated the impacts of crude oil price variations on Turkish stock market returns using vector autoregression model using daily observations of Brent crude oil prices and Istanbul Stock Exchange National Index returns.
Abstract: The purpose of this study is to investigate the impacts of crude oil price variations on the Turkish stock market returns. We have employed vector autoregression model using daily observations of Brent crude oil prices and Istanbul Stock Exchange National Index returns for the period between January 2, 1990 and November 1, 2011. We have also tested the relationship between oil prices and stock market returns under global liquidity conditions by incorporating a liquidity proxy variable, Chicago Board of Exchange’s SP Stock Returns; Global Liquidity JEL Classifications: C58; G15; Q43; Q47
32 citations
TL;DR: In this paper, the authors examined the time-varying levels of weak-form efficiency and the presence of structural breaks for two worldwide crude oil benchmarks over the period spanning from January 2, 1990, through September 18, 2012.
23 citations
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TL;DR: In this article, a forecast combination approach was proposed to predict quarterly real Brent oil prices, which reduced the forecast bias and predicted the direction of the oil price changes more accurately than both benchmarks.
Abstract: This paper demonstrates how the real-time forecasting accuracy of different Brent oil price forecast models changes over time. We find considerable instability in the performance of all models evaluated and argue that relying on average forecasting statistics might hide important information on a model's forecasting properties. To address this instability, we propose a forecast combination approach to predict quarterly real Brent oil prices. A four-model combination (consisting of futures, risk-adjusted futures, a Bayesian VAR and a DGSE model of the oil market) predicts Brent oil prices more accurately than the futures and the random walk up to 11 quarters ahead, on average, and generates a forecast whose performance is remarkably robust over time. In addition, the model combination reduces the forecast bias and predicts the direction of the oil price changes more accurately than both benchmarks.
22 citations
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TL;DR: In this paper, the authors explore the links between Brent crude oil index and stock markets index in OECD countries by employing a multivariate fractionally integrated asymmetric, power ARCH model with dynamic corrected conditional correlations of Engle (1982) M-FIAPARCH-c-DCCE with a Student-t distribution.
Abstract: This paper aims to explore the links between Brent crude oil index and stock markets index in OECD countries. We estimate time-varying conditional correlation relationships among these variables by employing a Multivariate Fractionally Integrated Asymmetric, Power ARCH model with dynamic corrected conditional correlations of Engle (1982) M-FIAPARCH-c-DCCE with a Student-t distribution. This process detects eventual volatility spillovers, asymmetries and persistence, which are typically observed in stock markets and oil prices. Our sample consists of monthly frequency stock indexes and oil price, covering 17 OECD countries for the period January, 1990- September, 2012. We find that at the beginning of our sample, oil has offered diversification opportunities with respect to the stock market, but this trend has been reversed in the last decade. We regroup the countries sample in 5 groups which present quite similar patterns of dynamic correlation between oil and their stock market and corroborate our geographical clustering by multivariate correlations among stock markets.
21 citations
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TL;DR: In this paper, an enhanced regime-switching model was proposed to investigate the relationship between oil price surges and stock market cycles in five oil-dependent countries over the period from January 1989 to December 2007.
Abstract: We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries over the period from January 1989 to December 2007. Our model accounts for the joint effects of the WTI (West Texas Intermediate) and Brent oil markets and allows to simultaneously capture asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behavior, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price shocks than during the bull market phases. Whether the effects of oil shocks are positive and negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.
14 citations
TL;DR: In this paper, the authors apply a quantile unit root with structural breaks approach to explore whether the international crude oil markets are better characterized as globalized or regionalized, and find that the spreads contain a unit root in the lower quantiles but display mean reversion behavior in the upper quantiles.
Abstract: This study applies a novel quantile unit root with structural breaks approach to explore whether the international crude oil markets are better characterized as ‘globalized’ or ‘regionalized’. By using the spreads between WTI and Brent crude oil prices as a benchmark, we find that the spreads contain a unit root in the lower quantiles but display mean reversion behaviour in the upper quantiles. However, instead of focusing on some selected (local) quantiles, the quantile Kolmogorov–Smirnov tests over a range of quantiles suggest that the price differentials are universally mean-reverting and, thus, provide strong support to the ‘globalization’ view.
14 citations
TL;DR: In this paper, the authors examined the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets using the generalized method of moments (GMM) approach.
Abstract: Purpose – The purpose of this paper is to examine the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets. In so doing, the paper addresses two important issues. First, whether there is a positive relationship between returns and trading volume in the crude oil futures markets. Second, whether information regarding trading volume contributes to forecasting the magnitude of return in the markets, an important issue because the ability of trading volume to predict returns imply market inefficiency. Design/methodology/approach – The paper used daily closing futures price and their corresponding trading volumes for WTI and Brent crude oil markets during the sample period January 2008 to May 2011. Both the log volume and the unexpected component of the detrended volume are used in the analysis in other to have robust alternative conclusion. The generalized method of moments (GMM) approach is used to examine the contemporaneous relationship be...
TL;DR: An empirical study of stable distribution and long-range correlation in Brent crude oil market was presented in this paper, which implies that there are patterns or trends in returns that persist over time.
Abstract: An empirical study of stable distribution and long-range correlation in Brent crude oil market was presented. First, it is found that the empirical distribution of Brent crude oil returns can be fitted well by a stable distribution, which is significantly different from a normal distribution. Second, the detrended fluctuation analysis for the Brent crude oil returns shows that there are long-range correlation in returns. It implies that there are patterns or trends in returns that persist over time. Third, the detrended fluctuation analysis for the Brent crude oil returns shows that after the financial crisis 2008, the Brent crude oil market becomes more persistence. It implies that the financial crisis 2008 could increase the frequency and strength of the interdependence and correlations between the financial time series. All of these findings may be used to improve the current fractal theories.
TL;DR: In this paper, the authors analyzed whether daily returns of Brent crude oil, dollar/yen foreign exchange, Dow&Jones Industrial Average Index and 12-month libor display power law features in the scaling exponent and probability distributions or not, using different methods.
Abstract: In this study, we analyzed whether daily returns of Brent crude oil, dollar/yen foreign exchange, Dow&Jones Industrial Average Index and 12-month libor display power law features in the scaling exponent and probability distributions or not, using different methods. Due to the fact that the simulated time series with different values showed the robustness of Higuchis Fractal Dimension and Pengs Statistic, we used these two models in the analysis of the scaling features of the returns. On the other hand, in order to examine power law behaviors of probability distributions, we estimated parameters of the alpha-stable distributions for the return series using the Ecf and Percentile methods. Results showed that the Brent crude oil and 12-month libor have a high persistency in the returns, while the dollar/yen foreign exchange and Dow&Jones Industrial Average Index returns have short memory. According to the alpha-stable parameter estimations, all of the return series have thicker tails than normal distribution. Similar to the highest persistency of 12-month libor returns in the scaling exponent analysis, we have seen that this variable also has the thickest tails in the probability distributions, meaning that 12-month libor returns have the highest power law features within the series.
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TL;DR: In this article, a forecast combination approach was proposed to predict quarterly real Brent oil prices, and the model combination reduced the forecast bias and predicted the direction of the oil price changes more accurately than both benchmarks.
Abstract: This paper demonstrates how the real-time forecasting accuracy of different Brent oil price forecast models changes over time. We find considerable instability in the performance of all models evaluated and argue that relying on average forecasting statistics might hide important information on a model`s forecasting properties. To address this instability, we propose a forecast combination approach to predict quarterly real Brent oil prices. A four-model combination (consisting of futures, risk-adjusted futures, a Bayesian VAR and a DGSE model of the oil market) predicts Brent oil prices more accurately than the futures and the random walk up to 11 quarters ahead, on average, and generates a forecast whose performance is remarkably robust over time. In addition, the model combination reduces the forecast bias and predicts the direction of the oil price changes more accurately than both benchmarks. JEL Classification: Q43, C43, E32
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TL;DR: In this article, the authors investigated if the world's major benchmark crude oil markets are integrated using the latest data and test the globalization hypothesis when effects from structural breaks are reflected in the test model.
Abstract: As spread between the WTI and Brent crude oil price is widening after early 2011, it could be that the price relationship between these crude oil is changing. To see if such change affected the price linkages among the international crude oil markets, this study investigates if the world's major benchmark crude oil markets are integrated using the latest data and test the globalization hypothesis when effects from structural breaks are reflected in the test model. The study reveals that while the Brent and Dubai crude oil markets continue to have a long-run relationship, the WTI no longer have a long-run relationship with the international crude oil market.
TL;DR: In this article, the authors used the concept of realized volatility to forecast value-at-risk (VaR) for ICE Brent Crude oil futures and examined sensitivities in the VaR forecasts across intra-daily sampling frequency used to calculate realized volatility.
Abstract: This paper is the first to use the concept of realized volatility to forecast Value-at-Risk (VaR) for ICE Brent Crude oil futures. We examine sensitivities in the VaR forecasts across intra-daily sampling frequency used to calculate realized volatility. We evaluate the VaR forecasts using Christoffersen's test for conditional coverage on quantiles of particular interest. Additionally, we examine a percentile–percentile plot of the VaR forecasts for all percentiles. The main empirical results show that very good VaR forecasts can be obtained using Gaussian critical values in combination with volatility forecasts based on realized volatility. An examination of the sampling frequency suggests that the most accurate VaR forecasts are obtained with a sampling frequency of between 1 and 10 min. This has important implications for practitioners operating in the financial oil sector.
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TL;DR: This article examined the dependence structure between world crudeoil prices using the D-vine copula based GARCH model to analyze three randomvariables, namely, Light crude futures 1-Pos (NYMEX), Brent crude futures (ICE), and Oman crude futures, and found that the ICE is animportant variable that governs the interactions in the dependence structures be-tween the NYMEX and the DME.
Abstract: This paper examines the dependence structure between world crudeoil prices using the D-vine copula based GARCH model to analyze three randomvariables, namely, Light crude futures 1-Pos (NYMEX), Brent crude futures 1-Pos (ICE), and Oman crude futures 1-Pos (DME). We nd that NYMEX{ICE,NYMEX{DME, and ICE{DME have relatively strong dependence. In addition,we nd the evidences for asymmetric tail dependence in each pair with the valuesof upper tail and lower tail dependences of three pair-copulas as being quite closeto each other. Therefore, our ndings support the "one great pool" hypothesis.Moreover, the results from the D-vine copula model indicate that the ICE is animportant variable that governs the interactions in the dependence structure be-tween the NYMEX and the DME. In other words, the change in the oil price ofthe ICE will impact quite signicantly the prices of the NYMEX and the DME.
TL;DR: This paper investigated the degree to which spot and futures markets in Brent oil are integrated and found that economic shocks that arise in one markets are typically transmitted to the other oil markets approximately one for one, typically within minutes.
Abstract: The degree to which spot and futures oil markets are integrated is an important issue to producers and consumers of oil, as well as speculators, arbitragers and policy makers. In this paper, we utilize intraday data to investigate the degree to which spot and futures markets in Brent oil are integrated. Our evidence confirms the previous findings that spot and futures markets are highly integrated. Economic shocks that arise in one markets are typically transmitted to the other oil markets approximately one for one, typically within minutes.
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TL;DR: In this article, the authors empirically investigated the crude oil market price behavior and proposed an econometrical GARCH model (Engle, 1982; Bollerslev, 1986) to forecast the volatility of this market.
Abstract: Crude Oil is a commodity with huge strategic importance to all countries in the world. But in the recent years, the oil market as well as all commodities market has crossed an intense period of changes due to a volatile international economic context. After a decade of rapid economic growth rates, China and the other emerging markets are slowing down. After a harsh and unpredictable crisis, the financial and commodity regulation has changed; the uncertainty and distrust have increased, and, implicitly, the prices volatility in financial and commodity markets has also increased. In this paper we empirically investigated the crude oil market price behaviour and proposed an econometrical GARCH model (Engle, 1982; Bollerslev, 1986) to forecast the volatility of this market. Our research questions are how crude oil price volatility has changed in the recent years? In order to answer to this question we developed an empirical analysis using daily future one month quotation of Brent, Dubai and WTI crude oil over the last three years. These quotations were extracted from Thomson-Reuters Database. Our results suggest a relatively small volatility in crude oil market on a short run with a price fluctuation around the level of 110 USD/barrel for Brent crude oil. Moreover, our final conclusion is that: the economic slowdown in emerging markets, but also the new regulations in commodity markets represent new challenges for economists and researchers, and ask for structural reforms to adjust to new context.
TL;DR: In this article, the optimal hedging ratio (OHR) for the Brent Crude Oil Futures using daily data over the period 1990/17/8-2014/11/3 was examined.
Abstract: This paper examines the optimal hedging ratio (OHR) for the Brent Crude Oil Futures using daily data over the period 1990/17/8-2014/11/3. To gain OHR, it is employed a Vector Autoregressive (VAR) and Vector Error Correction (VEC) and Baysian Vector Autoregressive (BVAR) models. At last, the efficiency of these calculated OHR are compared through Edrington's index.
15 Jun 2014
TL;DR: In this article, a unit root test is used to determine whether unit roots exist in benchmark crude oil prices allowing for the possibility of a structural break and non-stationary volatility, and the authors find that the global economy experiences shocks which have a transitory effect on WTI and Brent oil prices, thereby reverting to a long run trend whose path is determined by structural fundamentals.
Abstract: Given that energy prices are known to contain structural breaks and are also characterized by volatility that changes over time we address this gap by adopting a novel unit root test due to Cavaliere, Harvey, Leybourne and Taylor (2011), that unifies these characteristics together. This paper aims to determine whether unit roots exist in benchmark crude oil prices allowing for the possibility of a structural break and non-stationary volatility. The literature is far from a consensus on the unit root properties of crude oil prices, which may result from low power of unit root tests, due to the presence of structural breaks and possible non-stationary volatility which seem to plague crude oil prices. We find that using a novel and more appropriate unit root test that allows for nonstationary volatility the conclusions about persistence in crude oil prices can be drastically different. In general, our findings suggest that the global economy experiences shocks which have a transitory effect on WTI and Brent oil prices, thereby reverting to a long-run trend whose path is determined by structural fundamentals.
TL;DR: In this paper, the authors investigated the relationship between spot and futures prices in Brent Crude Oil Market using daily data over the period 1990/17/8-2014/11/3.
Abstract: This paper investigates the relationship between spot and futures prices in Brent Crude Oil Market using daily data over the period 1990/17/8-2014/11/3. The results of unit root test indicate that both of the spot and futures prices variables are non-stationary. The results of the Johansen cointegration test suggest that there is a long-run relationship between these variables. The dynamic Granger causality captured from the vector error correction model indicates strong bidirectional effects between the spot and futures price of Brent Crude Oil. The coefficient of the ECT and lagged explanatory variables are significant in both equations which indicates that long-run as well as shortrun bidirectional causalities between log of spot and futures price.
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TL;DR: In this paper, Bollinger bands are used for trading in the markets for WTI and Brent crude oil and the results indicate that the crude oil market may not be weak-form efficient, and they generate profits and Sharpe ratios significantly higher than those of randomly generated orders of approximately the same holding time.
Abstract: This article explores whether common technical trading strategies used in equity markets can be employed profitably in the markets for WTI and Brent crude oil. The strategies tested are Bollinger Bands, based on a mean-reverting hedge portfolio of WTI and Brent. The trading systems are tested with historical data from 1992 to 2013, representing 22 years of data and for various specifications. The hedge ratio for the crude oil portfolio is derived by using the Johansen procedure and a dynamic linear model with Kalman filtering. The significance of the results is evaluated with a bootstrap test in which randomly generated orders are employed. Results show that some setups of the system are able to be profitable over every five-year period tested. Furthermore they generate profits and Sharpe ratios that are significantly higher than those of randomly generated orders of approximately the same holding time. The best results with some Sharpe ratios in excess of three, are obtained when a dynamic linear model with Kalman filtering and maximum likelihood estimates of the unknown variance of the state equation is employed to constantly update the hedge ratio of the portfolio. The results indicate that the crude oil market may not be weak-form efficient.
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TL;DR: In this paper, the authors analyzed the evolution of the optimal hedge ratio and hedging effectiveness for the Brent crude oil and found a positive relationship between the estimation period and the hedge effectiveness, with important implications on risk management strategies.
Abstract: The main purpose of risk management is to reduce the cash-flows fluctuations of a company. In order to properly manage risks, the estimation of the optimal hedging ratio is needed. This paper analyzes the evolution of the optimal hedge ratio and hedging effectiveness for the Brent crude oil. Also, the relationship between the estimation period and hedge ratio, respective hedging effectiveness is studied. The results show that if the estimation period is increased, the mean and median of the hedge ratio decrease, converging to 1. Also, for longer estimation periods, the volatility of the optimal hedge ratio tends to decrease. It is found a positive relationship between the estimation period and the hedging effectiveness, with important implications on risk management strategies.
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TL;DR: Agarwal et al. as mentioned in this paper suggested some measures to jump-start agricultural growth in Vidarbha region of Maharashtra, where agriculture has been growing at an accelerated pace, especially after 2000.
Abstract: Agrarian stagnation was much the same in the Saurashtra region of Gujarat and the Vidarbha region of Maharashtra until 1990, and for similar reasons. Since then, Saurashtra's agriculture has been growing, especially after 2000, at an accelerated pace, while Vidarbha's farmers have continued to stagnate. This paper interrogates why, and suggests some measures to jump-start agricultural growth in Vidarbha.
TL;DR: The authors applied autoregressive heteroscedasticity (ARCH) family models for the purpose of comparing stylized facts such as volatility clustering, leverage effect, long memory volatility and risk-return tradeoff for energy and stock markets.
Abstract: This paper applies autoregressive heteroscedasticity (ARCH) family models for the purpose of comparing stylized facts such as volatility clustering, leverage effect, long memory volatility and risk-return tradeoff for energy and stock markets. Empirical results have found that the presences of volatility clustering in both markets and the impact of volatility shocks to the conditional volatility display hyperbolic rather than exponential rate of decay. Meanwhile, only stock markets denote the leverage effect, which implies that ‘bad’ news has a greater impact on volatility than ‘good’ news at the same magnitude. Additionally, empirical results also highlighted that Kerosene and Brent crude oil are the only energy commodities exhibit risk-return tradeoff. For forecast evaluations, the FIAPARCH model indicates superior out of sample forecasts over short and long time horizon for stock markets. Nevertheless, FIAPARCH model suits better over long term as compared to short term for energy markets. Fina...
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TL;DR: In this paper, the authors proposed a method to test whether price squeezes have occurred in Brent Crude and found that the evidence is consistent with the hypothesis of price manipulation and that the test provides a model and method for detecting such cases.
Abstract: Recent rapidly rising and volatile energy commodities prices and financial price manipulation scandals have brought the pricing mechanisms of crude oil derivatives to the fore of both popular press and policy initiatives. Among the most important of such commodities is Brent Crude. Brent Crude and its complex of derivative products make Brent Crude potentially more opaque and thus susceptible to price manipulation than other commodities. In spite of the importance of Brent to the world economy and world energy prices, and its complex of derivative pricing, relatively little work has been done to explore the potential for, and evidence of, price manipulation in the Brent Crude complex. This paper seeks to address this lack by proposing a method to test whether price squeezes have occurred in Brent Crude. This paper builds on previous work which proposed an a priori test for evidence of manipulation and the theory of storage. Previous work (Barrera-Rey and Seymour 1996) posited that the very close-to-delivery end of the forward curve for Brent should not be simultaneously in contango and backwardation, while other work (Geman and Smith 2012) proposed using an econometric prediction and a model based on the theory of storage to detect manipulation in commodity markets. Our work builds on these approaches by developing a more detailed model of calendar spreads in the Brent Crude complex. In Brent, a particular area of potential manipulation is from the relatively illiquid and more opaque physical OTC forward market (where prices are ‘assessed’ by Platts during a short ‘window’ of time) and the more liquid ICE futures market. Our model relates prompt ICE futures calendar spreads to prompt-over-dated OTC forward spreads. The model then tests whether the a priori indicators of manipulation as suggested by Barrera-Rey and Seymour are statistically consistent with the process which drives spreads historically. We find that in most all cases, the indicated period of manipulation is statistically different. We further investigate whether other factors, such as liquidity (volume and open interest) or world oil market conditions (using WTI spreads) or other forward market conditions could be driving our results. The statistical difference is found to be invariant to the inclusion of these other explanatory variables. We conclude that the evidence is consistent with the hypothesis of price manipulation and that the test provides a model and method for detecting such cases.
TL;DR: In this paper, the causality between the Brent crude oil futures returns and the returns of the largest Romanian oil company, OMV Petrom (SNP), using a GARCH model, was analyzed.
Abstract: The understanding of causal relationships between oil and stock markets is an important issue in portfolio management and energy hedging. The paper analyzes the causality between the Brent crude oil futures returns and the returns of the largest Romanian oil company, OMV Petrom (SNP). Using a GARCH model, we also examine the volatility spillovers between the two financial instruments.
10 Mar 2014
TL;DR: In this paper, the authors examined return and volatility predictability of continuous futures contracts within the European Union Emissions Trading System (EU ETS) and found that using exogenous inputs, in the form of electricity, coal, Brent oil and gas prices, yield better results than using autoregressive terms of the emission allowance data.
Abstract: In this thesis we examine return and volatility predictability of continuous futures contracts within the European Union Emissions Trading System (EU ETS). The market has been active for nine years and we examine whether it is more mature now compared to a few years ago when most existing research was carried out. We find that autoregressive terms are now significantly weaker compared to during the first phase of the ETS, which is seen as a sign that the market has become more efficient. As heteroskedasticity is observed, GARCH models are used to model and predict volatility. To predict returns, we find that using exogenous inputs, in the form of electricity, coal, Brent oil and gas prices, yield better results than using autoregressive terms of the emission allowance data. Based on the results, we suggest that exogenous variables may be used to predict the returns of carbon futures.