ENERGIES_9_621_CODES: MATLAB codes for computing electricity spot price forecasts from "Automated variable selection and shrinkage for day-ahead electricity price forecasting"

Bartosz Uniejewski, Jakub Nowotarski and Rafał Weron

HSC Software from Hugo Steinhaus Center, Wroclaw University of Science and Technology

Abstract: These Matlab scripts and functions compute electricity spot price forecasts using the Naive model, 10 different expert autoregression models, four variable selection methods (single-step elimination, stepwise regression) and five shrinkage techniques (ridge regression, LASSO, elastic nets) used in B. Uniejewski, J. Nowotarski, R. Weron (2016) Automated variable selection and shrinkage for day-ahead electricity price forecasting, Energies 9(8), 621 (http://dx.doi.org/10.3390/en9080621). The zip file includes three scripts (main_*.m) to run all computations, three functions (forecast*.m) to perform the forecasts, two files with flags (*Flags.mat) and four data files (*.txt) with electricity day-ahead prices and holiday dummies from the GEFCom2014 competition and Nord Pool.

Language: MATLAB
Requires: MATLAB (tested on MATLAB ver. R2018a).
Keywords: Electricity spot price; Day-ahead price; Forecasting; Autoregression; Ridge regression; LASSO; Elastic net (search for similar items in EconPapers)
Date: 2018-09-09
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http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/hscode/U ... 6_Energies_Codes.zip Zipped file (application/zip)

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