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

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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)

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.

Suggested Citation

  • Mustafa Gülerce & Gazanfer Ünal, 2018. "Electricity price forecasting using multiple wavelet coherence method: Comparison of ARMA versus VARMA," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-20, March.
    • Handle: RePEc:wsi:ijfexx:v:05:y:2018:i:01:n:s2424786318500044
    DOI: 10.1142/S2424786318500044
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