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Title:On the realized volatility of the ECX CO2 Emissions 2008 Futures Contract: distribution, dynamics and forecasting PDF Logo
Authors:Chevallier, Julien
Sévi, Benoît
Issue Date:2009
Series/Report no.:Nota di lavoro // Fondazione Eni Enrico Mattei: Sustainable development 113.2009
Abstract: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.
Subjects:CO2 Price
Realized Volatility
HAR-RV
GARCH
Futures Trading
Emissions Markets
EU ETS
Intraday data
Forecasting
JEL:C5
G1
Q4
Document Type:Working Paper
Appears in Collections:FEEM Working Papers, Fondazione Eni Enrico Mattei

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