Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices

Jakub Nowotarski and Rafał Weron

No HSC/14/03, HSC Research Reports from Hugo Steinhaus Center, Wroclaw University of Science and Technology

Abstract: We evaluate a recently proposed method for constructing prediction intervals, which utilizes the concept of quantile regression (QR) and a pool of point forecasts of different time series models.We find that in terms of interval forecasting of Nord Pool day-ahead prices the new QR-based approach significantly outperforms prediction intervals obtained from standard, as well as, semi-parametric autoregressive time series models.

Keywords: Electricity spot price; Prediction interval; Quantile regression; Forecasts combination (search for similar items in EconPapers)
JEL-codes: C22 C24 C53 Q47 (search for similar items in EconPapers)
Pages: 7 pages
Date: 2014-04-30
New Economics Papers: this item is included in nep-ecm, nep-ene and nep-for
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Citations: View citations in EconPapers (10)

Published as J. Nowotarski, R. Weron (2014) Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices, IEEE Conference Proceedings, 11th International Conference on the European Energy Market (EEM'14), DOI 10.1109/EEM.2014.6861285.

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