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Asymmetric multi-fractal cross-correlations of the price of electricity in the US with crude oil and the natural gas

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  • Kristjanpoller, Werner
  • Minutolo, Marcel C.

Abstract

The price of commodities are often difficult to forecast due to the underlying characteristics of the series such as autocorrelation, heteroskedasticity, and non-linearity. For many commodities, it is both socially and financially detrimental to have too much error in the forecasts. In the case of electricity production, both stock-outs and over production result in failure in the form of blackouts on one side and waste on the other. Therefore, it is desirable to improve the models that are used to forecast both the production and demand of electricity in order to optimize the match between supply and demand. To accomplish the aforementioned, understanding of the behavior of the commodity is necessary. In this paper, we apply a multi-fractal asymmetric detrended cross-correlation analysis to analyze the presence and asymmetry of the cross-correlations between the price of electricity in U.S. with respect to crude oil and natural gas markets. Our data draws from the major producers of electricity in the U.S. and evaluates the multi-fractal asymmetric detrended cross-correlation with respect to WTI and Natural Gas; both important inputs into the production of electricity. Our findings illustrate the fractal and cross-correlation relationship between electricity production and commodity prices.

Suggested Citation

  • Kristjanpoller, Werner & Minutolo, Marcel C., 2021. "Asymmetric multi-fractal cross-correlations of the price of electricity in the US with crude oil and the natural gas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    • Handle: RePEc:eee:phsmap:v:572:y:2021:i:c:s0378437121001023
    DOI: 10.1016/j.physa.2021.125830
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    Cited by:

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    2. Luo, Keyu & Ye, Yong, 2024. "How responsive are retail electricity prices to crude oil fluctuations in the US? Time-varying and asymmetric perspectives," Research in International Business and Finance, Elsevier, vol. 69(C).
    3. Qiao, Sen & Dang, Yi Jing & Ren, Zheng Yu & Zhang, Kai Quan, 2023. "The dynamic spillovers among carbon, fossil energy and electricity markets based on a TVP-VAR-SV method," Energy, Elsevier, vol. 266(C).
    4. Donglan Liu & Xin Liu & Kun Guo & Qiang Ji & Yingxian Chang, 2023. "Spillover Effects among Electricity Prices, Traditional Energy Prices and Carbon Market under Climate Risk," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
    5. Kojić, Milena & Schlüter, Stephan & Mitić, Petar & Hanić, Aida, 2022. "Economy-environment nexus in developed European countries: Evidence from multifractal and wavelet analysis," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).

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