IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v526y2019ics0378437119303024.html
   My bibliography  Save this article

Spatiotemporal dynamics analysis and systemic risk measurement of energy price system based on complex network

Author

Listed:
  • Xu, Hua
  • Wang, Minggang
  • Yang, Weiguo

Abstract

Multivariate time series contain rich information of corresponding complex systems. This paper proposes a new method to characterize the evolution and transition characteristics of the correlation modes for multivariate time series(ETCCMMTS). Based on ETCCMMTS, the characteristics of energy price systems are analyzed. The results show that energy price correlated modes exhibit co-movement, group-occurrence and the small-world property. The results prove that futures prices have the leading role, the crude oil futures price affects the stability of an energy price system, and the crude oil spot price has the highest clustering coefficient, whereas the heating oil futures price has the largest betweenness coefficient. The topological absorptive is introduced to measure the systemic risk, and the ”risk hopping” phenomenon is revealed. The recursive graph indicates that the fluctuations of energy price display not only short-range correlation for 1–2 months but also long-range correlation for 7–8 years. Additionally, the long-range correlation will lead to high systematic risk. In the course of energy price fluctuations, there is a total of 41 different types of correlation modes. The cumulative time of different correlation modes may result in a “cumulative time jump” and shows a linear growth in general. In addition, the topological structure of energy price correlated modal transition network (EPCMTN) is revealed.

Suggested Citation

  • Xu, Hua & Wang, Minggang & Yang, Weiguo, 2019. "Spatiotemporal dynamics analysis and systemic risk measurement of energy price system based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119303024
    DOI: 10.1016/j.physa.2019.03.067
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119303024
    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.2019.03.067?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.

    Citations

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


    Cited by:

    1. Xiong, Shi & Chen, Weidong, 2022. "A robust hybrid method using dynamic network analysis and Weighted Mahalanobis distance for modeling systemic risk in the international energy market," Energy Economics, Elsevier, vol. 109(C).
    2. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).

    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:526:y:2019:i:c:s0378437119303024. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.