Multivariate volatility modeling of electricity futures

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2011-063

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Forecasting Models; Simulation Methods ; Financial Econometrics
• Subject: electricity futures ; dynamic conditional correlations ; forecasting ; multiplicative component ; Termingeschäft ; Elektrizität ; Volatilität ; Stromtarif ; ARCH-Modell ; EU-Staaten

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bauwens, Luc ; Hafner, Christian M. ; Pierret, Diane
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2011

Further information

• Handle: http://hdl.handle.net/10419/56746
• Last update: 10.03.2025, 11:46 AM CET