Economics at your fingertips  

Forecasting daily spot prices in the Russian electricity market with the ARFIMA model

Yuri Balagula

Applied Econometrics, 2020, vol. 57, 89-101

Abstract: 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)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Full text (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:

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 ().

Page updated 2021-08-31
Handle: RePEc:ris:apltrx:0389