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Multivariate Volatility Modeling Of Electricity Futures

Listed author(s):
  • Luc Bauwens
  • Christian M. Hafner
  • Diane Pierret

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.

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File URL: http://hdl.handle.net/10.1002/jae.2280
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 28 (2013)
Issue (Month): 5 (08)
Pages: 743-761

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Handle: RePEc:wly:japmet:v:28:y:2013:i:5:p:743-761
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