SEVI Benoit

The purpose of this paper is to investigate, for the first time, whether the next day’s consumption of natural gas can be accurately forecast using a simple model that solely incorporates the information contained in dayahead market data. Hence, unlike standard models that use a number of meteorological variables, we only consider two predictors: the price of natural gas and the spark ratio measuring the relative price of electricity to gas. We develop a suitable modeling approach that captures the essential features of daily gas consumption and, in particular, the nonlinearities resulting from power dispatching and apply it to the case of France. Our results document the existence of a long-run relation between demand and spot prices and provide estimates of the marginal impacts that these price variables have on observed demand levels. We also provide evidence of the pivotal role of the spark ratio in the short run which is found to have an asymmetric and highly nonlinear impact on demand variations. Lastly, we show that our simple model is sufficient to generate predictions that are considerably more accurate than the forecasts published by infrastructure operators.

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This paper thesis is composed of four self-contained chapters, contributing to the field of nonlinear econometrics. The first chapter focuses on the contribution of nonlinear econometrics through the measurement of financial performance using a dichotomous variable as the independent variable. The next three chapters are based on nonlinear regression models where the dichotomous variable is the dependent variable of the equation. Given the links between financial risk and the macroeconomic context, this part is linked to the theme of optimal allocation via the study of crises and recessions. This class of model (probit / logit) is used in the second chapter to study empirically the role of financial development in the probability of occurrence of banking crises. Then the last two chapters focus on the methodological framework developed by Kauppi and Saikkonen (2008) and Candelon, Dumitrescu and Hurlin (2012 . 2014) about forecasting business cycles from probit / logit models. Thus, the third chapter studies the empirical relationship linking the evolution of the credit spread and the future probability of expansion/recession in an extended data panel while testing the homogeneity of this relationship. Finally, the fourth chapter proposes a theoretical contribution by deriving the response functions of probit / logit models from the approach of Kauppi and Saikkonen (2008). These response functions are then used in an empirical framework to estimate the impact of an exogenous shock on the expansion/recession cycle.

The prevention of climate change is one of the priorities of the global energy policy, which aims to massively reduce greenhouse gas emissions. Faced with these challenges, it is striking that our knowledge of energy demand modeling remains imperfect because it is based largely on old empirical work and methodologies that are now outdated. The scientific objective of this thesis is twofold: to quantitatively analyze the economic determinants of energy demand and to develop new forecasting models. This thesis is structured in four chapters. The first chapter shows that natural gas consumption in France can be predicted with a simple model using only the information available to market participants. This chapter proves the existence of a long-term relationship between natural gas demand and the prices of other energies and provides estimates of their marginal impacts on observed demand levels. The second chapter empirically investigates the role of temperature in forecasting gas prices in the United States. It develops a methodology for constructing a new monthly temperature-based index. This index captures changes in the residual demand for natural gas in real time. It is used as an additional exogenous variable in structural VAR models to improve forecasts . and we show that these predictive models derived from structural models are improved by relying on real time data (not subject to revision). The third chapter proposes to use, in the case of oil, a structural model capturing expectations using non-causal VARs and to correctly identify the reactions of key oil variables to a news shock. The fourth chapter re-examines the predictive power of the convenience yield of oil and gas prices by incorporating expectations into an empirical specification, using a non-causal VAR based on storage theory that provides very competitive price forecasts in a simple bivariate framework.

The commercialization of microfinance has brought the financial performance of MFis to the forefront, with MFIs now adopting a commercial logic of profitability in addition to their established social logic of poverty alleviation. This poses a crucial management challenge for MFIs to balance the social and commercial aspects of their mission. This thesis aims to analyze how MFIs overcome their challenges to achieve their dual social and commercial goals. It uses the concept of bricolage as a theoretical perspective and an abductive, exploratory and qualitative methodological approach. The thesis also aims to provide a better understanding of the Cameroonian microfinance sector, in terms of its history and evolution, and the challenges specific to the sector. The study identifies various bricolage practices that MFIs use to advance their dual mission. The findings suggest that MFIs use these bricolage practices to mobilize resources, build legitimacy, and increase their or/reach, in a context characterized by resource constraints. These three bricolage outcomes reinforce each other to facilitate the MFIs' dual goals. This research also highlighted the four phases of evolution of the Cameroonian microfinance sector and the five main challenges facing MFIs in the sector. This thesis contributes to the literature on microfinance. It offers a new look at the management of the dual mission of MFIs by showing how MFIs mobilize do-it-yourself strategies to advance their social and business objectives. It highlights the link between the microfinance literature and bricolage.

Following the identification of certain cognitive aspects in economic decision making, several collective behaviors in economics and finance have been identified. Mimicry in the stock market is one of these manifestations, defined as the tendency of economic agents to follow their peers, sometimes ignoring information available to them. By examining the literature, this thesis identifies an inconsistency between the theoretical conception of mimicry and its empirical identification. Empirical models are divided into two categories: those focusing on investors (flows) and those examining returns. Existing empirical models for mimicry on returns do not consider mimicry at the micro level and some important factors, such as price variability, that affect the robustness of the methodology for identifying mimicry at the macro level, based on cross-sectional dispersion measures of returns. Using a combination of stock trading and stock returns data, this thesis first examines the inconsistency of the empirical results on micro-level mimicry with those on consensus returns. It is shown that micro-level mimicry, its direction (selling or buying) and the composition of the market (types of investors) affect the transmission mechanism from mimicry to consensus returns. Furthermore, a methodological examination of cross-sectional dispersion measures of stock returns reveals the weakness of existing empirical results due to the existence of a relationship between realized volatility and these same dispersion measures.

The weekly release of the U.S. inventory level by the DOE-EIA is known as the market mover in the U.S. oil futures market. We uncover suspicious trading patterns in the WTI futures markets in days when the inventory level is released that are higher than market forecasts: there are significantly more orders initiated by buyers in the two hours preceding the official release of the inventory level, with a drop in the average price of -0.25% ahead of the news release. This finding is consistent with informed trading. We also provide evidence of an asymmetric response of the oil price to oil-inventory news, and highlight an over-reaction that is partly compensated in the hours following the announcement.

The weekly release of the U.S. inventory level by the DOE-EIA is known as the market mover in the U.S. oil futures market. We uncover suspicious trading patterns in the WTI futures markets in days when the inventory level is released that are higher than market forecasts: there are significantly more orders initiated by buyers in the two hours preceding the official release of the inventory level, with a drop in the average price of –0.25% ahead of the news release. This finding is consistent with informed trading. We also provide evidence of an asymmetric response of the oil price to oil-inventory news, and highlight an over-reaction that is partly compensated in the hours following the announcement.

This thesis focuses on electricity spot markets and more particularly on their organization and design. Indeed, the electricity industry is facing new challenges due to the increase of renewable generation capacity but also due to more structural changes related to the behavior of actors. The first chapter of the thesis studies in detail the formation of liquidity in the German continuous market. In particular, it focuses on the evolution of the bid-ask spread during a trading session and the factors that influence it. In a second chapter, I quantitatively evaluate the effect of creating an auction before the start of a continuous market on liquidity, volatility and market concentration. The last part of the thesis theoretically studies the impact of vertical integration in sequential markets as well as the impact of real-time pricing for end consumers on the behavior of market participants.

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In this study, we assess the potential existence of private information on the level of (non-strategic) crude oil inventories in the United States by highlighting anomalies in past order flow and price movements in the two hours preceding the official Department of Energy (DOE) announcement.

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After having shown the existence of an inflationary impact of first generation biofuels on agricultural prices via a strengthening of the link between agricultural and oil prices, we highlight the absence of a real positive effect of their expansion on emerging and developing economies. Moreover, the rise in agricultural prices has forced some countries importing these agricultural products to implement policies to protect their domestic markets. These results prove that it is imperative to develop biofuel production that does not require food feedstocks. However, we highlight the preference of the French population for these second generation biofuels, especially for a production from agricultural residues. Finally, we establish - by taking the example of an American market - that the implementation of biofuel derivative markets in Europe could allow manufacturers to effectively protect themselves against price volatility.

This thesis aims to analyze the systemic risk on commodity futures markets. Indeed, several research works highlight the importance of these futures in the determination of the physical price of commodities. Their incorporation into traditional finance as a diversifying asset has led to a similar price evolution to that of various financial assets since about 2004. The question that motivated this thesis was therefore to quantify this systemic risk (since it affects commodities, which are directly involved in the real economy), to see precisely the means of transmission (which markets affect which other markets) and finally to allow for an evaluation of the consequences, for example, based on scenarios (stress tests). It therefore makes it possible to develop market surveillance tools and could therefore contribute to the regulation of these markets.

The purpose of this thesis is to study, in a context of financialization of commodity markets, certain strategies adopted by investors and their impact on volatility and excessive co-movement between energy and financial markets. To do this, three studies are proposed. The first one uses regime-switching models (MS-VAR) applied on a set of energy commodities and covers the period 1992-2017. The results suggest that during periods of high volatility, commercial agents (hedgers) play a crucial role in gas market price discovery. However, these hedging agents affect the proper functioning of other markets (oil, gasoline, fuel oil) and amplify their volatility. The second study deals with the GARCH ADCC versus GARCH DCC models on a sample of 17 countries and over the period 1997-2016. This study highlights the asymmetric effect of oil shocks on the conditional correlations of Asian and African markets, which can be explained by arbitrage activities and heterogeneous investor behavior. The third study focuses on staggered lag autoregressive models (ARDL) and reveals that after the financial crisis, and beyond macroeconomic and financial fundamentals, the index of excessive speculation explains, both in the long run and in the short run, the correlation between the oil market and the financial markets of some countries. This generates a phenomenon of excessive co-movement, and thus a financialization effect on these markets. Finally, we conclude the following: first, in times of high volatility, the gas market is a safe haven for financial investors. Second, investor behavior explains the excessive co-movement effect between the oil market and some financial markets. third, this excessive co-movement phenomenon limits the benefits of international portfolio diversification, especially during financial turbulence.

This PhD thesis is composed of three chapters, one article and two papers and is mainly related to the field of empirical financial econometrics. It analyzes the dependence and the link between the financial markets and the commodity markets, in particular the energy market. The distributions and correlations of the variables belonging to both markets are studied in order to determine their effects on each other and to analyze their trends to give a better insight into their behavior with respect to crises and abrupt events in the economy. These variables are represented by some financial indices (SP500, Euro stoxx 50, Msci China) as well as by the main commodity indices (SP GSCI, Brent Oil, Natural Gas, Precious Metals). We choose to model their correlation over time and to take into account the non-linearity and instability that can affect them. For this purpose, the copula function approach has been used to model their distributions in an efficient way. In the first chapter, we examine the dependence and co-movements between carbon dioxide emission prices and energy indices such as coal, natural gas, Brent oil and the global energy index. The second chapter analyzes the interactions and relationships between the oil market and two major financial markets in Europe and the United States represented by the Euro stoxx 50 and the SP500. The last chapter analyzes the multivariate dependence between commodity indices of different sectors with financial indices using the Regular Vine copula model.

This thesis focuses on the issue of financing the low-carbon energy transition and the role of the financial and banking sector in achieving international climate objectives. The challenges of the energy transition for the financial sector are threefold. First, it is necessary to understand the need to adopt a differentiated analysis of household energy consumption, in particular that related to housing, in the search for a balance between macroeconomic objectives and individual financial and economic trade-offs. The first chapter analyzes household energy expenditures by typology and proposes a segmentation of the microeconomic behaviors of the actors and of the energy transition market in housing. It is then necessary to find a way to enhance the value of private investments in energy transition, which are still difficult to massify, especially when it comes to the energy performance of housing. Chapter 2 deploys a model based on a frontier function optimization technique to account for the presence of a green value in a local private housing market in France. Finally, the multiple risks related to climate change must be integrated into the mapping of the final risks (specific, systematic and systemic) that weigh on financial institutions, in the evaluation of their activity (the management of financial flows) but also in the evaluation of the risk profile of their balance sheet. Financial intermediaries, but also the institutions that regulate them, have a key role to play in establishing a social value of carbon endogenous to financial markets (Chapter 3).

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The extraction of the jump component in dynamics of asset prices haw witnessed a considerably growing body of literature. Of particular interest is the decomposition of returns' quadratic variation between their continuous and jump components. Recent contributions highlight the importance of this component in forecasting volatility at different horizons. In this article, we extend a methodology developed in Maheu and McCurdy (2011) to exploit the information content of intraday data in forecasting the density of returns at horizons up to sixty days. We follow Boudt et al. (2011) to detect intraday returns that should be considered as jumps. The methodology is robust to intra-week periodicity and further delivers estimates of signed jumps in contrast to the rest of the literature where only the squared jump component can be estimated. Then, we estimate a bivariate model of returns and volatilities where the jump component is independently modeled using a jump distribution that fits the stylized facts of the estimated jumps. Our empirical results for S&P 500 futures, U.S. 10-year Treasury futures, USD/CAD exchange rate and WTI crude oil futures highlight the importance of considering the continuous/jump decomposition for density forecasting while this is not the case for volatility point forecast. In particular, we show that the model considering jumps apart from the continuous component consistenly deliver better density forecasts for forecasting horizons ranging from 1 to 30 days.

As speculative flows into commodity futures are expected to link commodity prices more strongly to equity indices, we investigate whether this process also creates increased correlations amongst the commodities themselves. Considering U.S. oil and gas futures, we investigate whether common factors, derived from a large international data set of real and nominal macroeconomic variables by means of the large approximate factor models methodology, are able to explain both returns and whether, beyond these fundamental common factors, the residuals remain correlated. We further investigate a possible explanation for this residual correlation by using some proxies for trading intensity derived from CFTC publicly available data, showing most notably that the proxy for speculation in the oil market increases the oil-gas correlation. We thus identify the central role of financial activities in shaping the link between oil and gas returns.

This thesis studies the role played by financial investors in commodity markets, known as commodity financialization. It consists of a theoretical and an empirical part. The research aims to study the participation of investors, holding equity portfolios, in commodity futures markets, for diversification reasons. Moreover, this diversification can be achieved by investing in a basket of commodities. The first chapter analyzes theoretically the interaction between the commodity and equity markets. The second chapter empirically studies the impact of financial investors' choice on the risk premium of commodity futures contracts. It focuses on three commodities: crude oil (WTI), heating oil and natural gas. The third chapter theoretically studies the integration of two commodity markets. We clarify some considerations regarding the effect of financialization on which the existing literature remains hesitant. We demonstrate the power of influence that investors have on the commodity market. However, this depends on the nature of the investor's position in the futures market. In general, financialization leads to higher spot prices, higher futures prices and higher inventory levels. We also show that investors represent a transmission channel between commodity markets. Their extended effects are limited to the cross-correlation of commodity markets. Finally, we show that equity market returns became a determinant of the futures risk premium after the 2008 financial crisis. This effect of equity returns is indifferent between short and long maturities.

We empirically reinvestigate the issue of the excess co-movement of commodity prices initially raised in Pindyck and Rotemberg (1990). Excess co-movement appears when commodity prices remain correlated even after adjusting for the impact of fundamentals. We use recent developments in large approximate factor models to consider a richer information set and adequately model these fundamentals. We consider a set of eight unrelated commodities along with 184 real and nominal macroeconomic variables, from developed and emerging economies, from which nine factors are extracted over the 1993–2013 period. Our estimates provide evidenceof time-varying excess co-movement which is particularly high after 2007. Wefurther show that speculative intensity is a driver of the estimated excess comovement, as speculative trading is both correlated across the commodity futures markets and correlated with the futures prices. Our results can be taken as direct evidence of the significant impact of financialization on commodity-price crossmoments.

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The weekly release of the U.S. inventory level by the DOE-EIA is known as the market mover in the U.S. oil futures market and to be a significant piece of information for all world oil markets in which the WTI is a price benchmark. We uncover suspicious trading patterns in the WTI futures markets in days when the inventory level is released that are higher than economists’ forecasts: there are significantly more orders initiated by buyers in the two hours preceding the official release of the inventory level. We also show a clear drop in the average price of -0.25% ahead of the news release. This finding is consistent with informed trading. We also provide evidence of an asymmetric response of the oil price to the news, and highlight an over-reaction that is partly compensated in the hours following the announcement.

No summary available.

The influence of oil price fluctuations has been the subject of numerous empirical studies, yet there is no consensus on the transmission mechanisms in the economy. The objective of this thesis is to identify the impact of oil price fluctuations on the real economy and stock markets of MENA countries. To this end, we first implement causality and cointegration tests to analyze the interactions between energy prices and macroeconomic variables in the short and long run respectively. Moreover, by dissociating the effects of oil price increases and decreases, we test the presence of asymmetric transmission of shocks on the economic variables of the region's exporting and importing countries. Second, we analyze the interdependencies between the stock market and the oil market through the estimation of a VAR(1)-GARCH(1,1) model with constant conditional correlation that takes into account the effects of shock transmission on the returns and volatilities of the two markets. We conduct both an aggregate and a sectoral analysis to detect the impact of energy price changes on national stock market indices and identify the most vulnerable economic sectors. Finally, the analysis of correlations between the stock market and the oil market provides useful information for portfolio diversification in the presence of risk related to oil price variations.

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We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1–66days using a variety of models relying on the decomposition of realized variance in its positive or negative (semivariances) part and its continuous or discontinuous part (jumps). We show the importance of these decompositions in predictive (in-sample) regressions using a number of specifications. Nevertheless, an important empirical finding comes from an out-of-sample analysis which unambiguously shows the limited interest of considering these components. Overall, our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance.

This paper evaluates the predictability of WTI light sweet crude oil futures by using the variance risk premium, i.e. the difference between model-free measures of implied and realized volatilities. Additional regressors known for their ability to explain crude oil futures prices are also considered, capturing macroeconomic, financial and oil-specific influences. The results indicate that the explanatory power of the (negative) variance risk premium on oil excess returns is particularly strong (up to 25% for the adjusted R-squared across our regressions). It complements other financial (e.g. default spread) and oil-specific (e.g. US oil stocks) factors highlighted in previous literature.

We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1-66days using a variety of models relying on the decomposition of realized variance in its positive or negative (semivariances) part and its continuous or discontinuous part (jumps). We show the importance of these decompositions in predictive (in-sample) regressions using a number of specifications. Nevertheless, an important empirical finding comes from an out-of-sample analysis which unambiguously shows the limited interest of considering these components. Overall, our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance.

This thesis studies the European electricity market. The first topic focuses on the interdependencies of electricity prices in the main European markets to assess the effectiveness of the reforms introduced by the European Commission to create a single electricity market. We use multivariate statistical methods (vector autoregressive model and Granger causality test). The second topic concerns the impact of the introduction of the derivatives market on the volatility of spot market prices through an econometric study with the GARCH model. The objective is to examine the stabilizing or destabilizing effect of derivatives on the volatility of electricity prices. Finally, the third topic analyzes the potential effects of the evolution of regulatory reforms on prices and security of supply as well as the interactions between the UK and EU reforms.

This paper considers the downside-risk aversion of investors as an explanation for the risk-return trade-off. We test empirically this hypothesis using intraday data along with the recent measure of downside-risk called realized semivariance developed in Barndorff-Nielsen et al. (2010). The empirical analysis over the period 1996–2008 provides evidence of a significant relation between semivariance and excess returns at the daily frequency. To gain better understanding of the relation between returns and downside-risk, we investigate the statistical relation between a new measure of conditional asymmetry, namely the ratio of the downside realized semivariance over the variance, and obtain a revealing pattern using a rolling window framework able to link asymmetry in the distribution to future returns. In particular, the asymmetry measure becomes significant when the past realized variance is not significant any more thereby providing insights about a possible change in the behavior of investors.

Patton and Sheppard (2011) develop the concept of signed jumps as the difference between positive and negative realized positive semivariances. This quantity is well-suited for gauging the risk-return trade-off at high-frequency as it is well-defined each day and, contrary to the squared jump contribution following Barndorff-Nielsen and Shephard (2004, 2006) which is dedicated to rare jumps, it is signed. We show that signed jumps only occasionally help in explaining future returns, at least when the horizon of interest is one-day ahead as in Bali and Peng (2006).

Since the middle of the 80s, particularly in Europe, the public energy R&D expenditures have noticeably slowed down. Meanwhile, the European deregulation of energy network activities and the consecutive restructuring of energy sectors has led companies to significantly reduce their R&D investments. What will be the consequences of the public and private declines in energy R&D on the output of new technical knowledge? We suggest that the private energy R&D restructuring might in the long term favour the exploitation strategies of companies to the detriment of their exploration strategies. We also examine whether specific incentives – intended to correct the present trend of energy R&D – have been and or should be implemented by the leading European countries.

We empirically reinvestigate the issue of excess comovement of commodity prices initially raised in Pindyck and Rotemberg (1990) and show that excess comovement, when it exists, can be related to hedging and speculative pressure in commodity futures markets. Excess comovement appears when commodity prices remain correlated even after adjusting for the impact of common factors. While Pindyck and Rotemberg and following c ontributions examine this issue using a relevant but arbitrary set of control variables, we use recent developments in large approximate factor models so that a richer information set can be considered and “fundamentals” are likely to be adequately modeled. We consider a set of 8 unrelated commodities along with 187 real and nominal macroeconomic variables from which 9 factors are extracted over the period 1993-2010. Our estimates provide evidence of a time-varying excess comovement which is only occasionally significant, even after controlling for heteroscedasticity. Interestingly, excess comovement is mostly significant in recent years when a large increase in the trading of commodities is observed and also in crisis periods. However, we show that this increase in trading activity alone has no explanatory power for the excess comovement. Conversely, measures of hedging and speculative pressure explain around 60% of the estimated ex cess comovement thereby showing the strong impact not only of the financialization process, but also the impact of behaviour of some categories of traders on the price of commodities and the fact that supply and demand variables are not the sole factors in determining equilibrium prices.

We empirically reinvestigate the issue of excess comovement of commodity prices initially raised in Pindyck and Rotemberg (1990) and show that excess comovement, when it exists, can be related to hedging and speculative pressure in commodity futures markets. Excess comovement appears when commodity prices remain correlated even after adjusting for the impact of common factors. While Pindyck and Rotemberg and following contributions examine this issue using a relevant but arbitrary set of control variables, we use recent developments in large approximate factor models so that a richer information set can be considered and "fundamentals" are likely to be adequately modeled. We consider a set of 8 unrelated commodities along with 187 real and nominal macroeconomic variables from which 9 factors are extracted over the period 1993-2010. Our estimates provide evidence of a time-varying excess comovement which is only occasionally significant, even after controlling for heteroscedasticity. Interestingly, excess comovement is mostly significant in recent years when a large increase in the trading of commodities is observed and also in crisis periods. However, we show that this increase in trading activity alone has no explanatory power for the excess comovement. Conversely, measures of hedging and speculative pressure explain around 60% of the estimated excess comovement thereby showing the strong impact not only of the financialization process, but also the impact of behaviour of some categories of traders on the price of commodities and the fact that supply and demand variables are not the sole factors in determining equilibrium prices.

This paper considers the downside-risk aversion of investors as an explanation for the risk-return trade-off. We test empirically this hypothesis using intraday data along with the recent measure of downside-risk called realized semivariance developed in Barndorff-Nielsen et al. (2010). The empirical analysis over the period 1996–2008 provides evidence of a significant relation between semivariance and excess returns at the daily frequency. To gain better understanding of the relation between returns and downside-risk, we investigate the statistical relation between a new measure of conditional asymmetry, namely the ratio of the downside realized semivariance over the variance, and obtain a revealing pattern using a rolling window framework able to link asymmetry in the distribution to future returns. In particular, the asymmetry measure becomes significant when the past realized variance is not significant any more thereby providing insights about a possible change in the behavior of investors.

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There are now a number of small or medium-scale experiments where individuals can actively participate in permit markets. Where individuals retain permits, the remaining quota for polluting firms is decreased thereby theoretically increasing global welfare. This result lies on two major hypothesis: first, citizens have rational expectations and, second, they are risk-neutral. In this article, we provide theoretical arguments about the potential welfare-decreasing impact of citizen's participation when at least one of these assumptions is violated. Importantly, our conclusions lead, in some particular cases, to recommend a limited participation of individuals in permit schemes while encouraging a better diffusion of information toward this class of potential participants. This is the case, for instance, when scientific uncertainty about a phenomenon is strong and citizens cannot estimate the marginal abatement cost with confidence.

Pricing carbon is a central concern in environmental economics, due to the worldwide importance of emissions trading schemes to regulate pollution. This paper documents the presence of small and large jumps in the stochastic process of the CO 2\₂ futures price. The large jumps have a discrete origin, i.e. they can arise from various demand factors or institutional decisions on the tradable permits market. Contrary to the existing literature, we show that the stochastic process of carbon futures prices does not contain a continuous component (Brownian motion). The results are derived by using high-frequency data in the activity signature function framework (Todorov and Tauchen in J Econom 154:125–138, 2010. Todorov and Tauchen in J Bus Econ Stat 29:356–371, 2011). The implication is that the carbon futures price should be modeled as an appropriately sampled, centered Lévy or Poisson process. The pure-jump behavior of the carbon price might be explained by the lower volume of trades on this allowance market (compared to other highly liquid financial markets).