Forecasting daily spot prices in the Russian electricity market with the ARFIMA model
Applied Econometrics, 2020, vol. 57, 89-101
The long memory phenomenon in time series of daily spot prices in the Russian electricity market is investigated. The forecasting performance of the ARFIMA model is assessed by cross-validation. The empirical results confirmed the presence of long memory in electricity prices and the best prediction accuracy of the ARFIMA model.
Keywords: ARFIMA; time series; long memory; electricity market (search for similar items in EconPapers)
JEL-codes: C22 C53 L94 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://pe.cemi.rssi.ru/pe_2020_57_089-101.pdf Full text (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0389
Access Statistics for this article
Applied Econometrics is currently edited by Anatoly Peresetsky
More articles in Applied Econometrics from Russian Presidential Academy of National Economy and Public Administration (RANEPA)
Bibliographic data for series maintained by Anatoly Peresetsky ().