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Statistical and nonlinear analyses of return volatility dynamics on energy futures

Author

Listed:
  • Guochao Wang

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

  • Shenzhou Zheng

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

  • Jun Wang

    (School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China)

Abstract

The energy markets, as important parts of global financial markets, have been regarded as complex nonlinear systems. The researches on the return volatility of energy futures are of great significance for grasping the law of operations and measuring the risks of markets. This paper introduces two novel volatility statistics — volatility two-component range intensity (VTRI) and cumulative volatility two-component range intensity (CVTRI) into energy futures markets to investigate the volatility dynamics of eight important energy futures. These two statistics combine the volatility shortest passage time (or volatility duration) with the volatility maximum change intensity and the volatility cumulative change intensity. Then, some statistical properties including probability distribution and tail power-law distribution of VTRI series and CVTRI series for eight energy futures are studied by some statistical analyses methods. Moreover, various nonlinear analytical methods are used to explore some nonlinear behaviors including correlation behavior, similarity behavior and multifractal property of VTRI series and CVTRI series.

Suggested Citation

  • Guochao Wang & Shenzhou Zheng & Jun Wang, 2019. "Statistical and nonlinear analyses of return volatility dynamics on energy futures," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(11), pages 1-26, November.
    • Handle: RePEc:wsi:ijmpcx:v:30:y:2019:i:11:n:s0129183119500840
    DOI: 10.1142/S0129183119500840
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    References listed on IDEAS

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