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• W2155482907 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." @default.
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• W2155482907 date "2005-05-01" @default.
• W2155482907 modified "2023-10-05" @default.
• W2155482907 title "A GARCH Forecasting Model to Predict Day-Ahead Electricity Prices" @default.
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• W2155482907 doi "https://doi.org/10.1109/tpwrs.2005.846044" @default.
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