IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v442y2016icp67-73.html
   My bibliography  Save this article

Compositional segmentation and complexity measurement in stock indices

Author

Listed:
  • Wang, Haifeng
  • Shang, Pengjian
  • Xia, Jianan

Abstract

In this paper, we introduce a complexity measure based on the entropic segmentation called sequence compositional complexity (SCC) into the analysis of financial time series. SCC was first used to deal directly with the complex heterogeneity in nonstationary DNA sequences. We already know that SCC was found to be higher in sequences with long-range correlation than those with low long-range correlation, especially in the DNA sequences. Now, we introduce this method into financial index data, subsequently, we find that the values of SCC of some mature stock indices, such as S&P500 (simplified with S&P in the following) and HSI, are likely to be lower than the SCC value of Chinese index data (such as SSE). What is more, we find that, if we classify the indices with the method of SCC, the financial market of Hong Kong has more similarities with mature foreign markets than Chinese ones. So we believe that a good correspondence is found between the SCC of the index sequence and the complexity of the market involved.

Suggested Citation

  • Wang, Haifeng & Shang, Pengjian & Xia, Jianan, 2016. "Compositional segmentation and complexity measurement in stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 67-73.
    • Handle: RePEc:eee:phsmap:v:442:y:2016:i:c:p:67-73
    DOI: 10.1016/j.physa.2015.08.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115007220
    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.2015.08.057?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. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    2. Sergio Arianos & Anna Carbone, 2008. "Cross-correlation of long-range correlated series," Papers 0804.2064, arXiv.org, revised Mar 2009.
    3. Aki-Hiro Sato, 2012. "A Comprehensive Analysis of Time Series Segmentation on the Japanese Stock Prices," Papers 1205.0332, arXiv.org, revised Mar 2013.
    4. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    5. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2012. "The Japanese economy in crises: A time series segmentation study," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-81.
    6. Kantelhardt, Jan W & Koscielny-Bunde, Eva & Rego, Henio H.A & Havlin, Shlomo & Bunde, Armin, 2001. "Detecting long-range correlations with detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 441-454.
    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. Yang, Pengbo & Shang, Pengjian & Lin, Aijing, 2017. "Financial time series analysis based on effective phase transfer entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 398-408.
    2. 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.
    3. Mao, Xuegeng & Shang, Pengjian, 2018. "Extended AIC model based on high order moments and its application in the financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 264-275.
    4. Li, Chao & Shang, Pengjian, 2018. "Complexity analysis based on generalized deviation for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 118-128.

    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. He, Hong-di & Wang, Jun-li & Wei, Hai-rui & Ye, Cheng & Ding, Yi, 2016. "Fractal behavior of traffic volume on urban expressway through adaptive fractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 518-525.
    2. Xia, Jianan & Shang, Pengjian & Lu, Dan & Yin, Yi, 2016. "A comprehensive segmentation analysis of crude oil market based on time irreversibility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 104-114.
    3. Dutta, Srimonti & Ghosh, Dipak & Chatterjee, Sucharita, 2016. "Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 188-201.
    4. Pavón-Domínguez, P. & Serrano, S. & Jiménez-Hornero, F.J. & Jiménez-Hornero, J.E. & Gutiérrez de Ravé, E. & Ariza-Villaverde, A.B., 2013. "Multifractal detrended fluctuation analysis of sheep livestock prices in origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4466-4476.
    5. Telesca, Luciano & Lovallo, Michele, 2010. "Long-range dependence in tree-ring width time series of Austrocedrus Chilensis revealed by means of the detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4096-4104.
    6. Saha, Debajyoti & Ghosh, Sabuj & Shaw, Pankaj Kumar & Janaki, M.S. & Iyengar, A.N.S., 2018. "Interplay of transitions between oscillations with emergence of fireballs and quantification of phase coherence, scaling index in a magnetized glow discharge plasma in a toroidal assembly," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 295-303.
    7. Chatterjee, Sucharita & Ghosh, Dipak, 2021. "Impact of Global Warming on SENSEX fluctuations — A study based on Multifractal detrended cross correlation analysis between the temperature anomalies and the SENSEX fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    8. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.
    9. Leonarduzzi, R. & Wendt, H. & Abry, P. & Jaffard, S. & Melot, C. & Roux, S.G. & Torres, M.E., 2016. "p-exponent and p-leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 319-339.
    10. Zhao, Xiaojun & Shang, Pengjian & Lin, Aijing & Chen, Gang, 2011. "Multifractal Fourier detrended cross-correlation analysis of traffic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3670-3678.
    11. Gulich, Damián & Zunino, Luciano, 2014. "A criterion for the determination of optimal scaling ranges in DFA and MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 17-30.
    12. Ghosh, Dipak & Dutta, Srimonti & Chakraborty, Sayantan, 2014. "Multifractal detrended cross-correlation analysis for epileptic patient in seizure and seizure free status," Chaos, Solitons & Fractals, Elsevier, vol. 67(C), pages 1-10.
    13. Chatterjee, Sucharita, 2020. "Analysis of the human gait rhythm in Neurodegenerative disease: A multifractal approach using Multifractal detrended cross correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    14. İşcanoğlu-Çekiç, Ayşegül & Gülteki̇n, Havva, 2019. "Are cross-correlations between Turkish Stock Exchange and three major country indices multifractal or monofractal?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 978-990.
    15. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    16. Lavička, Hynek & Kracík, Jiří, 2020. "Fluctuation analysis of electric power loads in Europe: Correlation multifractality vs. Distribution function multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    17. Sun, Yuxin & Ibikunle, Gbenga, 2017. "Informed trading and the price impact of block trades: A high frequency trading analysis," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 114-129.
    18. Koutmos, Dimitrios, 2012. "An intertemporal capital asset pricing model with heterogeneous expectations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1176-1187.
    19. Tobias J. Moskowitz & Mark Grinblatt, 2002. "What Do We Really Know About the Cross-Sectional Relation Between Past and Expected Returns?," Yale School of Management Working Papers ysm259, Yale School of Management.
    20. Seungwook Bahng, 2003. "Do Psychological Barriers Exist in the Stock Price Indices? Evidence from Asia's Emerging Markets," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 6(1), pages 35-52, March.

    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:442:y:2016:i:c:p:67-73. 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.