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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://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-063.pdf
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Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2011-063.

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Length: 28 pages
Date of creation: Oct 2011
Handle: RePEc:hum:wpaper:sfb649dp2011-063
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