Parametric density recalibration of a fundamental market model to forecast electricity prices

Bello, A, Bunn, D W, Reneses, J and Munoz, A (2016) Parametric density recalibration of a fundamental market model to forecast electricity prices. Energies, 9 (11). ISSN 1996-1073 OPEN ACCESS


This paper proposes a new approach to hybrid forecasting methodology, characterized as the statistical recalibration of forecasts from fundamental market price formation models. Such hybrid methods based upon fundamentals are particularly appropriate to medium term forecasting and in this paper the application is to month-ahead, hourly prediction of electricity wholesale prices in Spain. The recalibration methodology is innovative in seeking to perform the recalibration into parametrically defined density functions. The density estimation method selects from a wide diversity of general four-parameter distributions to fit hourly spot prices, in which the first four moments are dynamically estimated as latent functions of the outputs from the fundamental model and several other plausible exogenous drivers. The proposed approach demonstrated its effectiveness against benchmark methods across the full range of percentiles of the price distribution and performed particularly well in the tails.

More Details

Item Type: Article
Subject Areas: Management Science and Operations
Additional Information:

This article belongs to the Special Issue Forecasting Models of Electricity Prices:

Date Deposited: 13 Dec 2016 13:27
Date of first compliant deposit: 29 Nov 2016
Subjects: Price theory
Electricity supply industry
Last Modified: 21 Apr 2024 00:43

Export and Share


Published Version - Text
  • Available under License


View details on Dimensions' website

Downloads from LBS Research Online

View details

Actions (login required)

Edit Item Edit Item