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Multifractal diffusion entropy analysis on stock volatility in financial markets

Author

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  • Huang, Jingjing
  • Shang, Pengjian
  • Zhao, Xiaojun

Abstract

This paper introduces a generalized diffusion entropy analysis method to analyze long-range correlation then applies this method to stock volatility series. The method uses the techniques of the diffusion process and Rényi entropy to focus on the scaling behaviors of regular volatility and extreme volatility respectively in developed and emerging markets. It successfully distinguishes their differences where regular volatility exhibits long-range persistence while extreme volatility reveals anti-persistence.

Suggested Citation

  • Huang, Jingjing & Shang, Pengjian & Zhao, Xiaojun, 2012. "Multifractal diffusion entropy analysis on stock volatility in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5739-5745.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:22:p:5739-5745
    DOI: 10.1016/j.physa.2012.06.039
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    References listed on IDEAS

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    1. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    2. Gabaix, Xavier & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Stanley, H.Eugene, 2003. "Understanding the cubic and half-cubic laws of financial fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 1-5.
    3. 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.
    4. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    5. Gita Persand & Chris Brooks, 2003. "Volatility forecasting for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 1-22.
    6. Cai, Shi-Min & Zhou, Pei-Ling & Yang, Hui-Jie & Yang, Chun-Xia & Wang, Bing-Hong & Zhou, Tao, 2006. "Diffusion entropy analysis on the scaling behavior of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 337-344.
    7. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    8. Mizuno, Takayuki & Takayasu, Hideki & Takayasu, Misako, 2006. "Correlation networks among currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 336-342.
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    Citations

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    Cited by:

    1. Batra, Luckshay & Taneja, H.C., 2020. "Evaluating volatile stock markets using information theoretic measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    2. Maria C. Mariani & Peter K. Asante & Md Al Masum Bhuiyan & Maria P. Beccar-Varela & Sebastian Jaroszewicz & Osei K. Tweneboah, 2020. "Long-Range Correlations and Characterization of Financial and Volcanic Time Series," Mathematics, MDPI, vol. 8(3), pages 1-18, March.
    3. Liu, Zhengli & Shang, Pengjian & Wang, Yuanyuan, 2019. "Multifractal weighted permutation analysis based on Rényi entropy for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    4. He, Qian & Huang, Jingjing, 2020. "A method for analyzing correlation between multiscale and multivariate systems—Multiscale multidimensional cross recurrence quantification (MMDCRQA)," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    6. Daniel Chiew & Judy Qiu & Sirimon Treepongkaruna & Jiping Yang & Chenxiao Shi, 2019. "The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-22, April.
    7. Dai, Meifeng & Hou, Jie & Gao, Jianyu & Su, Weiyi & Xi, Lifeng & Ye, Dandan, 2016. "Mixed multifractal analysis of China and US stock index series," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 268-275.
    8. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    9. Rodriguez-Romo, Suemi & Sosa-Herrera, Antonio, 2013. "Lacunarity and multifractal analysis of the large DLA mass distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3316-3328.
    10. Petr Jizba & Jan Korbel, 2016. "Techniques for multifractal spectrum estimation in financial time series," Papers 1610.07028, arXiv.org.
    11. Yan, Ruzhen & Yue, Ding & Chen, Xudong & Wu, Xu, 2020. "Non-linear characterization and trend identification of liquidity in China's new OTC stock market based on multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    12. Gu, Danlei & Huang, Jingjing, 2019. "Multifractal detrended fluctuation analysis on high-frequency SZSE in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 225-235.
    13. Jizba, Petr & Korbel, Jan, 2014. "Multifractal diffusion entropy analysis: Optimal bin width of probability histograms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 438-458.
    14. He, Jiayi & Shang, Pengjian, 2017. "Comparison of transfer entropy methods for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 772-785.
    15. Huang, Jingjing & Shang, Pengjian, 2015. "Multiscale multifractal diffusion entropy analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 221-228.
    16. Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.
    17. Zhang, Yali & Shang, Pengjian & He, Jiayi & Xiong, Hui, 2020. "Cumulative Tsallis entropy based on multi-scale permuted distribution of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).

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