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Analysis of time series using a new entropy plane based on past entropy

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  • Qin, Guyue
  • Shang, Pengjian

Abstract

Complexity is an important feature of complex time series. This paper proposes a new entropy plane using past Tsallis entropy and past Re´nyi entropy by weighted permutation pattern (PTEWP and PREWP), to quantify the complexity of time series. Through simulated data and actual data, we have verified the effectiveness of the entropy plane method. The results show that the new entropy plane can be used as an effective tool to distinguish financial markets.

Suggested Citation

  • Qin, Guyue & Shang, Pengjian, 2021. "Analysis of time series using a new entropy plane based on past entropy," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921008316
    DOI: 10.1016/j.chaos.2021.111477
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    References listed on IDEAS

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    1. David Backus & Mikhail Chernov & Stanley Zin, 2014. "Sources of Entropy in Representative Agent Models," Journal of Finance, American Finance Association, vol. 69(1), pages 51-99, February.
    2. M. Mirali & S. Baratpour, 2017. "Dynamic version of weighted cumulative residual entropy," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(22), pages 11047-11059, November.
    3. Constantino Tsallis & Celia Anteneodo & Lisa Borland & Roberto Osorio, 2003. "Nonextensive statistical mechanics and economics," Papers cond-mat/0301307, arXiv.org.
    4. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    5. M. Mirali & S. Baratpour & V. Fakoor, 2017. "On weighted cumulative residual entropy," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(6), pages 2857-2869, March.
    6. Ponta, Linda & Murialdo, Pietro & Carbone, Anna, 2021. "Information measure for long-range correlated time series: Quantifying horizon dependence in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    7. 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.
    8. Linda Ponta & Anna Carbone, 2017. "Information measure for financial time series: quantifying short-term market heterogeneity," Papers 1710.07331, arXiv.org, revised Feb 2018.
    9. Asok Nanda & Prasanta Paul, 2006. "Some Properties of Past Entropy and their Applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 64(1), pages 47-61, August.
    10. Oh, Gabjin & Kim, Seunghwan & Eom, Cheoljun, 2007. "Market efficiency in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 209-212.
    11. Lan, Boon Leong & Tan, Ying Oon, 2007. "Statistical properties of stock market indices of different economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 605-611.
    12. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    13. Felix Belzunce & Jorge Navarro & José M. Ruiz & Yolanda del Aguila, 2004. "Some results on residual entropy function," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(2), pages 147-161, May.
    14. Dai, Yimei & He, Jiayi & Wu, Yue & Chen, Shijian & Shang, Pengjian, 2019. "Generalized entropy plane based on permutation entropy and distribution entropy analysis for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 217-231.
    15. Tsallis, Constantino & Anteneodo, Celia & Borland, Lisa & Osorio, Roberto, 2003. "Nonextensive statistical mechanics and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 89-100.
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    Cited by:

    1. Wang, Fang & Wang, Lin & Chen, Yuming, 2022. "Multi-affine visible height correlation analysis for revealing rich structures of fractal time series," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    2. Li, Sange & Shang, Pengjian, 2022. "A new complexity measure: Modified discrete generalized past entropy based on grain exponent," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).

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