Article (Scientific journals)
Multivariate Volatility Modeling of Electricity Futures
Bauwens, Luc; Hafner, Christian; Pierret, Diane
2013In Journal of Applied Econometrics, 28 (5), p. 743-761
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Abstract :
[en] We model the dynamic volatility and correlation structure of electricity futures of the European Energy Exchange index. We use a new multiplicative dynamic conditional correlation (mDCC) model to separate long-run from short-run components. We allow for smooth changes in the unconditional volatilities and correlations through a multiplicative component that we estimate nonparametrically. For the short-run dynamics, we use a GJR-GARCH model for the conditional variances and augmented DCC models for the conditional correlations. We also introduce exogenous variables to account for congestion and delivery date effects in short-term conditional variances. We find different correlation dynamics for long- and short-term contracts and the new model achieves higher forecasting performance compared \to a standard DCC model.
Disciplines :
Finance
Author, co-author :
Bauwens, Luc
Hafner, Christian
Pierret, Diane  ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
External co-authors :
yes
Language :
English
Title :
Multivariate Volatility Modeling of Electricity Futures
Publication date :
August 2013
Journal title :
Journal of Applied Econometrics
ISSN :
1099-1255
Publisher :
John Wiley & Sons, Hoboken, United States - New Jersey
Volume :
28
Issue :
5
Pages :
743-761
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Finance
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since 07 December 2022

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