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Electricity price forecasting using multiple wavelet coherence method: Comparison of ARMA versus VARMA

Mustafa Gülerce () and Gazanfer Ünal
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Mustafa Gülerce: Financial Economics Programme, Yeditepe University, İnönü Mah., Kayışdağı Cad. 326, 26 Ağustos Yerleşimi, 34755 Ataşehir/İstanbul, Turkey
Gazanfer Ünal: Financial Economics Programme, Yeditepe University, İnönü Mah., Kayışdağı Cad. 326, 26 Ağustos Yerleşimi, 34755 Ataşehir/İstanbul, Turkey

International Journal of Financial Engineering (IJFE), 2018, vol. 05, issue 01, 1-20

Abstract: The aim of this paper is to bring out a new perspective for Electricity price forecasting. Numerous studies have focused on forecasting the day-ahead or long-term price forecasting of electricity, rather than examine the relationship between energy commodities, by using various methods. Therefore, this study proposes a model-free approach for electricity price forcasting (EPF). The proposed approach is based on Partial Wavelet Coherency (PWC) and Multiple Wavelet Coherency (MWC) method. These methods are capable of uncovering the coherent time intervals simultaneously for time and frequency domains between the examined time series. VARMA uses the coherent time intervals and outperforms its univariate counterpart (ARMA), both in point and interval forecasting.

Keywords: ARMA and VARMA models; electricity market; energy pricing; wavelet coherence; price forecasting (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S2424786318500044

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