IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v572y2021ics0378437121001023.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121001023
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.125830?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    2. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.
    3. Wa̧torek, Marcin & Drożdż, Stanisław & Oświȩcimka, Paweł & Stanuszek, Marek, 2019. "Multifractal cross-correlations between the world oil and other financial markets in 2012–2017," Energy Economics, Elsevier, vol. 81(C), pages 874-885.
    4. Wang, Jie & Wang, Jun & Stanley, H. Eugene, 2018. "Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 889-902.
    5. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Pawe{l} O'swic{e}cimka & Marek Stanuszek, 2018. "Multifractal cross-correlations between the World Oil and other Financial Markets in 2012-2017," Papers 1812.08548, arXiv.org, revised Jun 2019.
    6. Pawe{l} O'swik{e}cimka & Stanis{l}aw Dro.zd.z & Mattia Frasca & Robert Gk{e}barowski & Natsue Yoshimura & Luciano Zunino & Ludovico Minati, 2020. "Wavelet-based discrimination of isolated singularities masquerading as multifractals in detrended fluctuation analyses," Papers 2004.03319, arXiv.org.
    7. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    8. Jiang, Jiaqi & Gu, Rongbao, 2016. "Asymmetrical long-run dependence between oil price and US dollar exchange rate—Based on structural oil shocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 75-89.
    9. Moyano, L.G. & de Souza, J. & Duarte Queirós, S.M., 2006. "Multi-fractal structure of traded volume in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(1), pages 118-121.
    10. Zhi-Qiang Jiang & Wen-Jie Xie & Wei-Xing Zhou & Didier Sornette, 2018. "Multifractal analysis of financial markets," Papers 1805.04750, arXiv.org.
    11. Ma, Feng & Wei, Yu & Huang, Dengshi & Zhao, Lin, 2013. "Cross-correlations between West Texas Intermediate crude oil and the stock markets of the BRIC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5356-5368.
    12. B. Podobnik & I. Grosse & D. Horvatić & S. Ilic & P. Ch. Ivanov & H. E. Stanley, 2009. "Quantifying cross-correlations using local and global detrending approaches," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 243-250, September.
    13. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    14. Gajardo, Gabriel & Kristjanpoller, Werner, 2017. "Asymmetric multifractal cross-correlations and time varying features between Latin-American stock market indices and crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 121-128.
    15. Zhang, Chen & Ni, Zhiwei & Ni, Liping, 2015. "Multifractal detrended cross-correlation analysis between PM2.5 and meteorological factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 114-123.
    16. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.
    17. Fan, Qingju, 2016. "Asymmetric multiscale detrended fluctuation analysis of California electricity spot price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 252-260.
    18. Stanislaw Drozdz & Jaroslaw Kwapien & Pawel Oswiecimka & Rafal Rak, 2009. "Quantitative features of multifractal subtleties in time series," Papers 0907.2866, arXiv.org, revised Feb 2010.
    19. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    20. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    21. Gajardo, Gabriel & Kristjanpoller, Werner D. & Minutolo, Marcel, 2018. "Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 195-205.
    22. Cao, Guangxi & Cao, Jie & Xu, Longbing & He, LingYun, 2014. "Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 460-469.
    23. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    2. 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).
    3. 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.
    4. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    3. Kristjanpoller, Werner & Bouri, Elie, 2019. "Asymmetric multifractal cross-correlations between the main world currencies and the main cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1057-1071.
    4. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    5. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    6. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    8. Gajardo, Gabriel & Kristjanpoller, Werner D. & Minutolo, Marcel, 2018. "Does Bitcoin exhibit the same asymmetric multifractal cross-correlations with crude oil, gold and DJIA as the Euro, Great British Pound and Yen?," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 195-205.
    9. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    10. Guo, Yaoqi & Yu, Zhuling & Yu, Chenxi & Cheng, Hui & Chen, Weixun & Zhang, Hongwei, 2021. "Asymmetric multifractal features of the price–volume correlation in China’s gold futures market based on MF-ADCCA," Research in International Business and Finance, Elsevier, vol. 58(C).
    11. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    12. Wang, Qizhen, 2019. "Multifractal characterization of air polluted time series in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 167-180.
    13. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    14. Jiang, Jiaqi & Gu, Rongbao, 2016. "Asymmetrical long-run dependence between oil price and US dollar exchange rate—Based on structural oil shocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 75-89.
    15. Li, Shuping & Li, Jianfeng & Lu, Xinsheng & Sun, Yihong, 2022. "Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    16. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.
    17. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    18. Hasan, Rashid & Mohammed Salim, M., 2017. "Power law cross-correlations between price change and volume change of Indian stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 620-631.
    19. Gajardo, Gabriel & Kristjanpoller, Werner, 2017. "Asymmetric multifractal cross-correlations and time varying features between Latin-American stock market indices and crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 121-128.
    20. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:572:y:2021:i:c:s0378437121001023. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.