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

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.

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Year of publication:	2014-04-30
Authors:	Nowotarski, Jakub ; Weron, Rafal
Institutions:	Hugo Steinhaus Center for Stochastic Methods, Politechnika Wrocławska
Subject:	Electricity spot price \| Prediction interval \| Quantile regression \| Forecasts combination

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Extent:	application/pdf
Series:	HSC Research Reports.
Type of publication:	Book / Working Paper
Notes:	Forthcoming in IEEE Conference Proceedings, 11th International Conference on the European Energy Market (EEM'14). Number HSC/14/03 7 pages
Classification:	C22 - Time-Series Models ; C24 - Truncated and Censored Models ; C53 - Forecasting and Other Model Applications ; q47
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010765436