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Extreme-volatility dynamics in crude oil markets

Author

Listed:
  • Xiong-Fei Jiang

    (School of Information Engineering, Ningbo Dahongying University
    Research Center for Finance Computing, Ningbo Dahongying University
    Zhejiang University)

  • Bo Zheng

    (Zhejiang University
    Collaborative Innovation Center of Advanced Microstructures)

  • Tian Qiu

    (School of Information Engineering, Nanchang Hangkong University)

  • Fei Ren

    (School of Business, East China University of Science and Technology)

Abstract

Based on concepts and methods from statistical physics, we investigate extreme-volatility dynamics in the crude oil markets, using the high-frequency data from 2006 to 2010 and the daily data from 1986 to 2016. The dynamic relaxation of extreme volatilities is described by a power law, whose exponents usually depend on the magnitude of extreme volatilities. In particular, the relaxation before and after extreme volatilities is time-reversal symmetric at the high-frequency time scale, but time-reversal asymmetric at the daily time scale. This time-reversal asymmetry is mainly induced by exogenous events. However, the dynamic relaxation after exogenous events exhibits the same characteristics as that after endogenous events. An interacting herding model both with and without exogenous driving forces could qualitatively describe the extreme-volatility dynamics.

Suggested Citation

  • Xiong-Fei Jiang & Bo Zheng & Tian Qiu & Fei Ren, 2017. "Extreme-volatility dynamics in crude oil markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(2), pages 1-7, February.
    • Handle: RePEc:spr:eurphb:v:90:y:2017:i:2:d:10.1140_epjb_e2017-70482-4
    DOI: 10.1140/epjb/e2017-70482-4
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    Cited by:

    1. Yan Li & Bo Zheng & Ting-Ting Chen & Xiong-Fei Jiang, 2017. "Fluctuation-driven price dynamics and investment strategies," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
    2. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    3. Jiang, Xiong-Fei & Xiong, Long & Cen, Tao & Bai, Ling & Zhao, Na & Zhang, Jiu & Zheng, Chang-Juan & Jiang, Tian-Ying, 2022. "Analyst sentiment and earning forecast bias in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    4. Chen, Ting-Ting & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2018. "Information driving force and its application in agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 593-601.

    More about this item

    Keywords

    Statistical and Nonlinear Physics;

    Statistics

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