Analysis of Forecasting Models in an Electricity Market under Volatility

22 Pages Posted: 19 Mar 2021

See all articles by Gazi Salah Uddin

Gazi Salah Uddin

Linkoping University - Department of Management and Engineering Division

Maziar Sahamkhadam

Linnaeus University

Farhad Taghizadeh-Hesary

Tokai University

Muhammad Yahya

Inland Norway University of Applied Sciences

Ou Tang

Linkoping University

Pontus Cerin

Linkoping University

Jakob Rehme

Linkoping University

Date Written: January 13, 2021

Abstract

Short-term electricity price forecasting has received considerable attention in recent years. Despite this increased interest, the literature lacks a concrete consensus on the most suitable forecasting approach. We conduct an extensive empirical analysis to evaluate the short-term price forecasting dynamics of different regions in the Swedish electricity market (SEM). We utilized several forecasting approaches ranging from standard conditional volatility models to wavelet-based forecasting. In addition, we performed out-of-sample forecasting and back-testing, and we evaluated the performance of these models. Our empirical analysis indicates that an ARMA-GARCH framework with the student’s t-distribution significantly outperforms other frameworks. We only performed wavelet-based forecasting based on the MAPE. The results of the robust forecasting methods are capable of displaying the importance of proper forecasting process design, policy implications for market efficiency, and predictability in the SEM.

Keywords: forecasting, Swedish electricity market, GARCH modeling, multi-scale analysis, Gazi Salah Uddin, Ou Tang, Maziar Sahamkhadam, Farhad Taghizadeh-Hesary, Muhammad Yahya, Pontus Cerin, Jakob Rehme

JEL Classification: C53, G17

Suggested Citation

Uddin, Gazi Salah and Sahamkhadam, Maziar and Taghizadeh-Hesary, Farhad and Yahya, Muhammad and Tang, Ou and Cerin, Pontus and Rehme, Jakob, Analysis of Forecasting Models in an Electricity Market under Volatility (January 13, 2021). ADBI Working Paper 1212, Available at SSRN: https://ssrn.com/abstract=3807052 or http://dx.doi.org/10.2139/ssrn.3807052

Gazi Salah Uddin (Contact Author)

Linkoping University - Department of Management and Engineering Division ( email )

Linköping, 581 83
Sweden

Maziar Sahamkhadam

Linnaeus University ( email )

Växjö, S-35195
Sweden

Farhad Taghizadeh-Hesary

Tokai University ( email )

3-20-1 Orido
Shimizu-ku
Shizuoka, 424-8610
Japan

Muhammad Yahya

Inland Norway University of Applied Sciences ( email )

Ou Tang

Linkoping University ( email )

Överstegatan 30
Linkoping, 581 83
Sweden

Pontus Cerin

Linkoping University ( email )

Överstegatan 30
Linkoping, 581 83
Sweden

Jakob Rehme

Linkoping University ( email )

Överstegatan 30
Linkoping, 581 83
Sweden

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