Probabilistic forecasting with a hybrid Factor-QRA approach: Application to electricity trading

Katarzyna Maciejowska, Tomasz Serafin and Bartosz Uniejewski

Papers from arXiv.org

Abstract: This paper presents a novel hybrid approach for constricting probabilistic forecasts that combines both the Quantile Regression Averaging (QRA) method and the factor-based averaging scheme. The performance of the approach is evaluated on data sets from two European energy markets - the German EPEX SPOT and the Polish Power Exchange (TGE). The results show that the newly proposed method outperforms literature benchmarks in terms of statistical measures: the empirical coverage and the Christoffersen test for conditional coverage. Moreover, in line with recent literature trends, the economic value of forecasts is evaluated based on the trading strategy using probabilistic price predictions to optimize the operation of an energy storage system. The results suggest that apart from the use of statistical measures, there is a need for the economic evaluation of forecasts.

Date: 2023-03, Revised 2024-11
New Economics Papers: this item is included in nep-ene and nep-for
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Published in Electric Power Systems Research 2024, 234, 110541

Downloads: (external link)
http://arxiv.org/pdf/2303.08565 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2303.08565

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators (help@arxiv.org).