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

The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities.CO2 Price; Realized Volatility; HAR-RV; GARCH; Futures Trading; Emissions Markets; EU ETS; Intraday data; Forecasting

On the volatility-volume relationship in energy futures markets using intraday data

This paper investigates the relationship between trading volume and price volatility in the crude oil and natural gas futures markets when using high-frequency data. By regressing various realized volatility measures (with/without jumps) on trading volume and trading frequency, our results feature a contemporaneous and largely positive relationship. Furthermore, we test whether the volatility-volume relationship is symmetric for energy futures by considering positive and negative realized semivariance. We show that (i) an asymmetric volatility-volume relationship indeed exists, (ii) trading volume and trading frequency significantly affect negative and positive realized semivariance, and (iii) the information content of negative realized semivariance is higher than for positive realized semivariance.Trading Volume; Price Volatility; Crude Oil Futures; Natural Gas Futures; High-Frequency Data; Realized Volatility; Bipower Variation; Median Realized Volatility; Realised Semivariance; Jump

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

The recent implementation of the EU Emissions Trading Scheme (EU ETS) in January 2005 created new financial risks for emitting firms. To deal with these risks, options are traded since October 2006. Because the EU ETS is a new market, the relevant underlying model for option pricing is still a controversial issue. This article improves our understanding of this issue by characterizing the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European Climate Exchange (ECX), which is valid during Phase II (2008-2012) of the EU ETS. The realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-distributions hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability. Our conclusions indicate that (i) the standard Brownian motion is not an adequate tool for option pricing in the EU ETS, and (ii) a jump component should be included in the stochastic process to price options, thus providing more efficient tools for risk-management activities.CO2 Price, Realized Volatility, HAR-RV, GARCH, Futures Trading, Emissions Markets, EU ETS, Intraday data, Forecasting

The EU ETS: CO2 prices drivers during the learning experience (2005-2007)

This chapter identifies the main price drivers of European Union Allowances (EUAs), valid for compliance under the European Union Emissions Trading Scheme (EU ETS) created in 2005 to regulate CO2 emissions of more than 10,000 high carbon-intensive installations across Member States. Based on key design features of the EU ETS, this chapter develops carbon pricing strategies based on allowances supply and demand, institutional decisions, and the influence of other energy markets and weather conditions. Finally, we discuss the likely effects on economic growth on CO2 emissions and carbon prices as a by product. The discussions developed in this chapter focus on Phase I (2005-2007) of the EU ETS, which may described as the “pilot” period for the future development of this environmental market scheme.EU ETS; Cap-and-Trade Program; Climate Change Policy; CO2 Price; Energy Markets; Weather Influences; Institutional Influences; Energy Policy

Do jumps help in forecasting the density of returns?.

The estimation of the jump component in asset pricing has witnessed a considerably growing body of literature. Of particular interest is the decomposition of total volatility between its continuous and jump components. Recent contributions highlight the importance of the jump component in forecasting the volatility at different horizons. In this paper, we extend the methodology developed by Maheu and McCurdy (2011) to measure the information content of intraday data in forecasting the density of returns at horizons up to sixty days. We extract jumps as in Andersen, Bollerslev, Frederiksen and Nielsen (2010) to have a measure of the jumps in returns. Then, we estimate a bivariate model of returns and volatilities where the jump component is indepen- dently modeled. Our empirical results for S&P 500 futures, WTI crude oil futures, the USD/JPY exchange rate and the MacDonald’s stock confirm the importance of considering the continuous/jump decomposition for density forecasting.bivariate model; median realized volatility; bipower variation; realized volatility; jumps; density forecasting;

Forecasting world and regional aviation Jet-Fuel demands to the mid term (2025).

This article provides jet fuel demand projections at the worldwide level and for eight geographical zones until 2025. Air traffic forecasts are performed using dynamic panel-data econometrics. Then, the conversion of air traffic projections into quantities of jet fuel is accomplished by using a complementary approach to the ‘Traffic Efficiency’ method developed previously by the UK Department of Trade and Industry to support the Intergovernmental Panel on Climate Change (IPCC, 1999). According to our main scenario, air traffic should increase by about 100% between 2008 and 2025 at the world level, corresponding to a yearly average growth rate of 4.7%. World jet fuel demand is expected to increase by about 38% during the same period, corresponding to a yearly average growth rate of 1.9% per year. According to these results, energy efficiency improvements allow reducing the effect of air traffic rise on the increase in jet fuel demand, but do not annihilate it. Jet fuel demand is thus unlikely to diminish unless there is a radical technological shift, or air travel demand is restricted.Energy efficiency; Jet fuel demand forecasts; Macro-level methodology;

European carbon prices fundamentals in 2005-2007: the effects of energy markets, temperatures and sectorial production.

This article aims at characterizing the daily price fundamentals of European Union Allowances (EUAs) traded since 2005 as part of the Emissions Trading Scheme (ETS). First, the presence of two structural changes on April, 2006 following the disclosure of 2005 veri?ed emissions and on October, 2006 following the European Commission announcement of stricter Phase II allocation allow to isolate distinct fundamentals evolv- ing overtime. The results extend previous literature by showing that spot prices react not only to other energy markets and temperatures, but also to economic activity within the main sectors covered by the EU ETS such as proxied by sectoral production indices. Besides, the sub-period decomposition of the pilot phase gives a better grasp of institutional and market events that drive allowance price changes.Carbon Emissions Trading; EU ETS; Market Price Fundamentals;

Sparse Image Representation with Epitomes

Sparse coding, which is the decomposition of a vector using only a few basis elements, is widely used in machine learning and image processing. The basis set, also called dictionary, is learned to adapt to specific data. This approach has proven to be very effective in many image processing tasks. Traditionally, the dictionary is an unstructured "flat" set of atoms. In this paper, we study structured dictionaries which are obtained from an epitome, or a set of epitomes. The epitome is itself a small image, and the atoms are all the patches of a chosen size inside this image. This considerably reduces the number of parameters to learn and provides sparse image decompositions with shiftinvariance properties. We propose a new formulation and an algorithm for learning the structured dictionaries associated with epitomes, and illustrate their use in image denoising tasks.Comment: Computer Vision and Pattern Recognition, Colorado Springs : United States (2011

Monetary Exchange with Multilateral Matching

This paper analyzes monetary exchange in a search model allowing for multilateral matches to be formed, according to a standard urn-ballprocess. We consider three physical environments: indivisible goods and money, divisible goods and indivisible money, and divisible goods and money. We compare the results with Kiyotaki and Wright (1993), Trejos and Wright (1995), and Lagos and Wright (2005) respectively. We find that the multilateral matching setting generates very simple and intuitive equilibrium allocations that are similar to those in the other papers, but which have important differences. In particular, surplus maximization can be achieved in this setting, in equilibrium, with a positive money supply. Moreover, with flexible prices and directed search, the first best allocation can be attained through price posting or through auctions with lotteries, but not through auctions without lotteries. Finally, analysis of the case of divisible goods and money can be performed without the assumption of large families (as in Shi (1997)) or the day and night structure of Lagos and Wright (2005).monetary exchange; directed search; ex post bidding; multilateral matching

Options Introduction and Volatility in the EU ETS

To improve risk management in the European Union Emissions Trading Scheme (EU ETS), the European Climate Exchange (ECX) has introduced option instruments in October 2006 after regulatory authorization. The central question we address is: can we identify a potential destabilizing effect of the introduction of options on the underlying market (EU ETS futures)? Indeed, the literature on commodities futures suggest that the introduction of derivatives may either decrease (due to more market depth) or increase (due to more speculation) volatility. As the identification of these effects ultimately remains an empirical question, we use daily data from April 2005 to April 2008 to document volatility behavior in the EU ETS. By instrumenting various GARCH models, endogenous break tests, and rolling window estimations, our results overall suggest that the introduction of the option market had no effect on the volatility in the EU ETS. These finding are robust to other likely influences linked to energy and commodity markets.EU ETS, Option prices, Volatility, GARCH, Rolling Estimation, Endogenous Structural Break Detection