Forecasting of daily electricity prices with factor models: Utilizing intra-day and inter-zone relationships
AbstractWe show that incorporating the intra-day and inter-zone relationships of electricity prices in the Pennsylvania--New Jersey--Maryland (PJM) Interconnection improves the accuracy of short- and medium-term forecasts of average daily prices for a major PJM market hub -- the Dominion Hub in Virginia, U.S. The forecasting performance of four multivariate models calibrated to hourly and/or zonal day-ahead prices is evaluated and compared with that of a univariate model, which uses only average daily data for the Dominion Hub. The multivariate competitors include a restricted vector autoregressive model and three factor models with the common and idiosyncratic components estimated using principal components in a semiparametric setup. The results indicate that there are forecast improvements from incorporating the additional information, essentially for all considered forecast horizons ranging from one day to two months, but only when the correlation structure of prices across locations and hours is modeled using factor models.
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Bibliographic InfoPaper provided by Hugo Steinhaus Center, Wroclaw University of Technology in its series HSC Research Reports with number HSC/13/11.
Length: 19 pages
Date of creation: 30 Dec 2013
Date of revision:
Wholesale electricity price; Forecasting; Vector autoregression; Factor model; Principal components; PJM market;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-01-10 (All new papers)
- NEP-ENE-2014-01-10 (Energy Economics)
- NEP-FOR-2014-01-10 (Forecasting)
- NEP-ORE-2014-01-10 (Operations Research)
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