IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v143y2021ics0960077920308031.html
   My bibliography  Save this article

Multiscale Rényi cumulative residual distribution entropy: Reliability analysis of financial time series

Author

Listed:
  • Xu, Meng
  • Shang, Pengjian
  • Zhang, Sheng

Abstract

In the study of the complexity of time series, information measurement is an effective method to quantify the reliability of dynamic systems, such as financial markets, and its practical use is to identify the state of systems. In this paper, we propose a modification of cumulative residual entropy (CRE) based on cumulative distribution of a random variable, called multiscale Rényi cumulative residual distribution entropy (MRCE), to investigate information content found in more general cases. The CRE is a relevant dynamic measure of uncertainty in reliability studies. Rényi entropy and distribution entropy (DistEn) present diverse means to characterize different complexity behaviors of time series. Compared with the previous complex dynamics methods, the MRCE has larger range showing time series patterns in the field of parameterized transformation. Therefore, MRCE combines the multiscale theory and Rényi cumulative residual distribution entropy (RCE). It is applied to classical discrete distributions, synthetic series and real-world data. Results reveal that MRCE allows a high sensitivity to the predetermined parameters. The improved method enables us to further analyse the complexity of different time series at different scales. Simultaneously, financial time series of stock markets in the same region exhibit obvious similarities.

Suggested Citation

  • Xu, Meng & Shang, Pengjian & Zhang, Sheng, 2021. "Multiscale Rényi cumulative residual distribution entropy: Reliability analysis of financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    • Handle: RePEc:eee:chsofr:v:143:y:2021:i:c:s0960077920308031
    DOI: 10.1016/j.chaos.2020.110410
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920308031
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2020.110410?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.

    References listed on IDEAS

    as
    1. Kizilkale, Arman C. & Dimitrakopoulos, Roussos, 2014. "Optimizing mining rates under financial uncertainty in global mining complexes," International Journal of Production Economics, Elsevier, vol. 158(C), pages 359-365.
    2. Engelbert Stockhammer & Lucas Grafl, 2010. "Financial Uncertainty and Business Investment," Review of Political Economy, Taylor & Francis Journals, vol. 22(4), pages 551-568.
    3. Mathai, A.M. & Haubold, H.J., 2007. "Pathway model, superstatistics, Tsallis statistics, and a generalized measure of entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 110-122.
    4. Dong-Ming Song & Michele Tumminello & Wei-Xing Zhou & Rosario N. Mantegna, 2011. "Evolution of worldwide stock markets, correlation structure and correlation based graphs," Papers 1103.5555, arXiv.org.
    5. Liu, Zhengli & Shang, Pengjian, 2018. "Generalized information entropy analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1170-1185.
    6. Osvaldo Rosso & Felipe Olivares & Luciano Zunino & Luciana Micco & André Aquino & Angelo Plastino & Hilda Larrondo, 2013. "Characterization of chaotic maps using the permutation Bandt-Pompe probability distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(4), pages 1-13, April.
    7. Podobnik, Boris & Horvatic, Davor & Lam Ng, Alfonso & Eugene Stanley, H. & Ivanov, Plamen Ch., 2008. "Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3954-3959.
    8. Erin Lockwood, 2015. "Predicting the unpredictable: Value-at-risk, performativity, and the politics of financial uncertainty," Review of International Political Economy, Taylor & Francis Journals, vol. 22(4), pages 719-756, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mao, Xuegeng & Shang, Pengjian & Xu, Meng & Peng, Chung-Kang, 2020. "Measuring time series based on multiscale dispersion Lempel–Ziv complexity and dispersion entropy plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    2. Wang, Luo-Qing & Xu, Yong-Xiang, 2018. "Distribution of individual status in the invisibility similarity network of new social strata in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 426-434.
    3. Wu, Tao & Gao, Xiangyun & An, Sufang & Liu, Siyao, 2021. "Time-varying pattern causality inference in global stock markets," International Review of Financial Analysis, Elsevier, vol. 77(C).
    4. Longfeng Zhao & Wei Li & Andrea Fenu & Boris Podobnik & Yougui Wang & H. Eugene Stanley, 2017. "The q-dependent detrended cross-correlation analysis of stock market," Papers 1705.01406, arXiv.org, revised Jun 2017.
    5. Engelbert Stockhammer, 2009. "The finance-dominated accumulation regime, income distribution and the present crisis," Papeles de Europa, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Estudios Internacionales (ICEI), vol. 19, pages 58-81.
    6. El Alaoui, Marwane & Benbachir, Saâd, 2013. "Multifractal detrended cross-correlation analysis in the MENA area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5985-5993.
    7. Nobi, Ashadun & Maeng, Seong Eun & Ha, Gyeong Gyun & Lee, Jae Woo, 2014. "Effects of global financial crisis on network structure in a local stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 135-143.
    8. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    9. Philipp Heimberger & Jakob Kapeller, 2017. "The performativity of potential output: pro-cyclicality and path dependency in coordinating European fiscal policies," Review of International Political Economy, Taylor & Francis Journals, vol. 24(5), pages 904-928, September.
    10. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    11. Bastidon, Cécile & Parent, Antoine & Jensen, Pablo & Abry, Patrice & Borgnat, Pierre, 2020. "Graph-based era segmentation of international financial integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    12. Han, Jung Hun, 2013. "Gamma function to Beck–Cohen superstatistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4288-4298.
    13. Dai, Peng-Fei & Xiong, Xiong & Zhou, Wei-Xing, 2021. "A global economic policy uncertainty index from principal component analysis," Finance Research Letters, Elsevier, vol. 40(C).
    14. Kang, Sang Hoon & Yoon, Seong-Min, 2008. "Long memory features in the high frequency data of the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5189-5196.
    15. Zhang, Xin & Podobnik, Boris & Kenett, Dror Y. & Eugene Stanley, H., 2014. "Systemic risk and causality dynamics of the world international shipping market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 43-53.
    16. Li, Shuping & Lu, Xinsheng & Li, Jianfeng, 2021. "Cross-correlations between the P2P interest rate, Shibor and treasury yields," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    17. James, Nick & Menzies, Max & Gottwald, Georg A., 2022. "On financial market correlation structures and diversification benefits across and within equity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    18. Yerali Gandica & Marco Valerio Geraci & Sophie Béreau & Jean-Yves Gnabo, 2018. "Fragmentation, integration and macroprudential surveillance of the US financial industry: Insights from network science," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    19. A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Dynamic structural and topological phase transitions on the Warsaw Stock Exchange: A phenomenological approach," Papers 1301.6506, arXiv.org.
    20. Al Rahahleh, Naseem & Bhatti, M. Ishaq, 2017. "Co-movement measure of information transmission on international equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 119-131.

    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:chsofr:v:143:y:2021:i:c:s0960077920308031. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.