IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v502y2018icp248-255.html
   My bibliography  Save this article

Time irreversibility of financial time series based on higher moments and multiscale Kullback–Leibler divergence

Author

Listed:
  • Li, Jinyang
  • Shang, Pengjian

Abstract

Irreversibility is an important property of time series. In this paper, we propose the higher moments and multiscale Kullback–Leibler divergence to analyze time series irreversibility. The higher moments Kullback–Leibler divergence (HMKLD) can amplify irreversibility and make the irreversibility variation more obvious. Therefore, many time series whose irreversibility is hard to be found are also able to show the variations. We employ simulated data and financial stock data to test and verify this method, and find that HMKLD of stock data is growing in the form of fluctuations. As for multiscale Kullback–Leibler divergence (MKLD), it is very complex in the dynamic system, so that exploring the law of simulation and stock system is difficult. In conventional multiscale entropy method, the coarse-graining process is non-overlapping, however we apply a different coarse-graining process and obtain a surprising discovery. The result shows when the scales are 4 and 5, their entropy is nearly similar, which demonstrates MKLD is efficient to display characteristics of time series irreversibility.

Suggested Citation

  • Li, Jinyang & Shang, Pengjian, 2018. "Time irreversibility of financial time series based on higher moments and multiscale Kullback–Leibler divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 248-255.
  • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:248-255
    DOI: 10.1016/j.physa.2018.02.099
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118301869
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2018.02.099?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. Koissi, Marie-Claire & Shapiro, Arnold F. & Hognas, Goran, 2006. "Evaluating and extending the Lee-Carter model for mortality forecasting: Bootstrap confidence interval," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 1-20, February.
    2. Chen, Yi-Ting & Chou, Ray Y. & Kuan, Chung-Ming, 2000. "Testing time reversibility without moment restrictions," Journal of Econometrics, Elsevier, vol. 95(1), pages 199-218, March.
    3. Lucas Lacasa & Ryan Flanagan, 2016. "Irreversibility of financial time series: a graph-theoretical approach," Papers 1601.01980, arXiv.org.
    4. Mike Buckle & Jing Chen & Julian M. Williams, 2016. "Realised higher moments: theory and practice," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1272-1291, October.
    5. Jing Wang & Pengjian Shang & Xiaojun Zhao & Jianan Xia, 2013. "Multiscale Entropy Analysis Of Traffic Time Series," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-14.
    6. Yin, Yi & Shang, Pengjian, 2015. "Modified cross sample entropy and surrogate data analysis method for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 17-25.
    7. Cammarota, Camillo & Rogora, Enrico, 2007. "Time reversal, symbolic series and irreversibility of human heartbeat," Chaos, Solitons & Fractals, Elsevier, vol. 32(5), pages 1649-1654.
    8. Ramsey, James B. & Rothman, Philip, 1988. "Characterization Of The Time Irreversibility Of Economic Time Series: Estimators And Test Statistics," Working Papers 88-39, C.V. Starr Center for Applied Economics, New York University.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alexander Bulinski & Denis Dimitrov, 2021. "Statistical Estimation of the Kullback–Leibler Divergence," Mathematics, MDPI, vol. 9(5), pages 1-36, March.
    2. Wu, Yue & Shang, Pengjian & Chen, Shijian, 2019. "Modified multifractal large deviation spectrum based on CID for financial market system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1331-1342.
    3. Jessica Morales Herrera & Ra'ul Salgado-Garc'ia, 2023. "Trend patterns statistics for assessing irreversibility in cryptocurrencies: time-asymmetry versus inefficiency," Papers 2307.08612, arXiv.org.

    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. Wu, Zhenyu & Shang, Pengjian & Xiong, Hui, 2018. "An improvement of the measurement of time series irreversibility with visibility graph approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 370-378.
    2. Huang, Yong & Yang, Dongqing & Wang, Lei & Wang, Kehong, 2020. "Classifying of welding time series based on multi-scale time irreversibility analysis and extreme learning machine," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Olivares, Felipe & Sun, Xiaoqian & Wandelt, Sebastian & Zanin, Massimiliano, 2023. "Measuring landing independence and interactions using statistical physics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    4. Rong, Lei & Shang, Pengjian, 2018. "New irreversibility measure and complexity analysis based on singular value decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 913-924.
    5. Gilles Zumbach, 2007. "Time reversal invariance in finance," Papers 0708.4022, arXiv.org.
    6. Yin, Yi & Shang, Pengjian & Ahn, Andrew C. & Peng, Chung-Kang, 2019. "Multiscale joint permutation entropy for complex time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 388-402.
    7. li, Chao & Shang, Pengjian, 2019. "Multiscale Tsallis permutation entropy analysis for complex physiological time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 10-20.
    8. Xiong, Hui & Shang, Pengjian & Xia, Jianan & Wang, Jing, 2018. "Time irreversibility and intrinsics revealing of series with complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 241-249.
    9. Jessica Morales Herrera & Ra'ul Salgado-Garc'ia, 2023. "Trend patterns statistics for assessing irreversibility in cryptocurrencies: time-asymmetry versus inefficiency," Papers 2307.08612, arXiv.org.
    10. Kuan Chung-Ming & Lee Wei-Ming, 2004. "A New Test of the Martingale Difference Hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-26, December.
    11. repec:zbw:bofrdp:1995_009 is not listed on IDEAS
    12. D’Amato, Valeria & Haberman, Steven & Piscopo, Gabriella & Russolillo, Maria, 2012. "Modelling dependent data for longevity projections," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 694-701.
    13. Hunt, Andrew & Villegas, Andrés M., 2015. "Robustness and convergence in the Lee–Carter model with cohort effects," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 186-202.
    14. Koissi, Marie-Claire & Shapiro, Arnold F., 2006. "Fuzzy formulation of the Lee-Carter model for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 39(3), pages 287-309, December.
    15. Zacharias Psaradakis & Marián Vávra, 2022. "Using Triples to Assess Symmetry Under Weak Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1538-1551, October.
    16. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    17. Beare, Brendan K. & Seo, Juwon, 2014. "Time Irreversible Copula-Based Markov Models," Econometric Theory, Cambridge University Press, vol. 30(5), pages 923-960, October.
    18. Renshaw, A.E. & Haberman, S., 2008. "On simulation-based approaches to risk measurement in mortality with specific reference to Poisson Lee-Carter modelling," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 797-816, April.
    19. Ugofilippo Basellini & Søren Kjærgaard & Carlo Giovanni Camarda, 2020. "An age-at-death distribution approach to forecast cohort mortality," Working Papers axafx5_3agsuwaphvlfk, French Institute for Demographic Studies.
    20. Man Chung Fung & Gareth W. Peters & Pavel V. Shevchenko, 2016. "A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting," Papers 1605.09484, arXiv.org.
    21. Lee, Yung-Tsung & Wang, Chou-Wen & Huang, Hong-Chih, 2012. "On the valuation of reverse mortgages with regular tenure payments," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 430-441.

    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:phsmap:v:502:y:2018:i:c:p:248-255. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.