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A GARCH forecasting model to predict day-ahead electricity prices
- Source :
- IEEE Transactions on Power Systems. May, 2005, Vol. 20 Issue 2, p867, 8 p.
- Publication Year :
- 2005
-
Abstract
- Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize profits. This paper provides an approach to predict next-day electricity prices based on the Generalized Autoregressive Conditional Heteroskedastic (GARCH) methodology that is already being used to analyze time series data in general. A detailed explanation of GARCH models is presented and empirical results from the mainland Spain and California deregulated electricity-markets are discussed. Index Terms--Electricity markets, forecasting, GARCH models, time series analysis, volatility.
Details
- Language :
- English
- ISSN :
- 08858950
- Volume :
- 20
- Issue :
- 2
- Database :
- Gale General OneFile
- Journal :
- IEEE Transactions on Power Systems
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.132477108