Understanding volatility dynamics in the EU-ETS market: lessons from the future
AbstractIn this paper we study the short term price behavior of December 2008 future prices for EU emission allowances. We model returns and volatility dynamics of this price showing that a standard ARMA-GARCH framework is not adequate and that the gaussianity assumption is rejected due to the occurrence of a number of level and volatility outliers. To improve the fitness of the model, we combine the underlying price process with an additive stochastic jump process. The resulting distribution, a mixture of Gaussians, allows for endogenously determined jumps in the process governing the returns, while the mixing law determines the jump probability. The performance of the model is improved by introducing a time varying jump probability explained by two variables. The first one is the daily relative change in the volume of transactions and suggests that sharp increases in volume increase volatility even in the absence of changes in what recent literature considers as market fundamentals. The second one accounts for changes in the jump probability associated to the European Commission's announcements regarding the NAPs for Phase II. We find that announcements concerning the NAPs induce jumps in the process and tend to increase volatility. This result suggests authorities should advocate to increase stability in the regulatory environment which is crucial to allow traders to realize efficient trading strategies and informed investment decisions regarding pollution reduction.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2009024.
Date of creation: 01 Apr 2009
Date of revision:
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EUA market; EU-ETS; carbon emission trading; Garch model; normal mixture;
Find related papers by JEL classification:
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Costs; Distributional Effects; Employment Effects
- Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-28 (All new papers)
- NEP-ENE-2010-03-28 (Energy Economics)
- NEP-ENV-2010-03-28 (Environmental Economics)
- NEP-EUR-2010-03-28 (Microeconomic European Issues)
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- Marc Gronwald & Janina Ketterer, 2009. "Evaluating Emission Trading as a Policy Tool - Evidence from Conditional Jump Models," CESifo Working Paper Series 2682, CESifo Group Munich.
- Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo Group Munich.
- Marc Gronwald & Janina Ketterer, 2009. "Zur Bewertung von Emissionshandel als Politikinstrument," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 62(11), pages 22-25, 06.
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