IDEAS home Printed from https://ideas.repec.org/a/rfa/bmsjnl/v3y2017i2p61-77.html
   My bibliography  Save this article

Autosimilarty, Long Memory and Chaos: Evidence from the Tunisian Market

Author

Listed:
  • Monia Antar Limam

Abstract

Fractal Finance came to the rescue of the classical models unable to explain financial anomalies and of linear models inadequate to characterize complex processes. The characterization of financial series is still topical. The calculation of the Hurst exponent, the fractal dimension, the Lyapunov exponent, the window of Theiler and the realization of the determinism test, have allowed us to understand the dynamics of the Tunisian indexes returns. Clearly, findings show that the returns are, on the one hand, nonlinear, follow alpha-stable laws, have a long memory and on the other hand, are not chaotic. Thus, the hypothesis of a Brownian fractal motion is privileged.

Suggested Citation

  • Monia Antar Limam, 2017. "Autosimilarty, Long Memory and Chaos: Evidence from the Tunisian Market," Business and Management Studies, Redfame publishing, vol. 3(2), pages 61-77, June.
  • Handle: RePEc:rfa:bmsjnl:v:3:y:2017:i:2:p:61-77
    as

    Download full text from publisher

    File URL: http://redfame.com/journal/index.php/bms/article/view/2449/2584
    Download Restriction: no

    File URL: http://redfame.com/journal/index.php/bms/article/view/2449
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Opong, Kwaku K. & Mulholland, Gwyneth & Fox, Alan F. & Farahmand, Kambiz, 1999. "The behaviour of some UK equity indices: An application of Hurst and BDS tests1," Journal of Empirical Finance, Elsevier, vol. 6(3), pages 267-282, September.
    2. Isabelle Girerd-Potin & Ollivier Taramasco, 1994. "Les rentabilités à la bourse de Paris sont-elles chaotiques ?," Revue Économique, Programme National Persée, vol. 45(2), pages 215-238.
    3. Hayek, F. A., 2012. "Hayek on Hayek," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226321202 edited by Kresge, Stephen & Wenar, Leif, December.
    4. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    5. J.A. Hołyst & M. Żebrowska & K. Urbanowicz, 2001. "Observations of deterministic chaos in financial time series by recurrence plots, can one control chaotic economy?," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 531-535, April.
    6. Wen, Xiaoqian & Wei, Yu & Huang, Dengshi, 2012. "Measuring contagion between energy market and stock market during financial crisis: A copula approach," Energy Economics, Elsevier, vol. 34(5), pages 1435-1446.
    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. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.

    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. Guglielmo Maria Caporale & Luis A. Gil‐Alana & James C. Orlando, 2016. "Linkages Between the US and European Stock Markets: A Fractional Cointegration Approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 143-153, April.
    2. Onali, Enrico & Goddard, John, 2009. "Unifractality and multifractality in the Italian stock market," International Review of Financial Analysis, Elsevier, vol. 18(4), pages 154-163, September.
    3. Batten, Jonathan A. & Ellis, Craig & Fetherston, Thomas A., 2005. "Return anomalies on the Nikkei: Are they statistical illusions?," Chaos, Solitons & Fractals, Elsevier, vol. 23(4), pages 1125-1136.
    4. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
    5. Jamdee, Sutthisit & Los, Cornelis A., 2007. "Long memory options: LM evidence and simulations," Research in International Business and Finance, Elsevier, vol. 21(2), pages 260-280, June.
    6. Ritesh Kumar Mishra & Sanjay Sehgal & N.R. Bhanumurthy, 2011. "A search for long‐range dependence and chaotic structure in Indian stock market," Review of Financial Economics, John Wiley & Sons, vol. 20(2), pages 96-104, May.
    7. Ivani Bora & Naliniprava Tripathy, 2016. "Random or Deterministic? Evidence from Indian Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(4), pages 1716-1721.
    8. Cal Muckley, 2004. "Empirical asset return distributions: is chaos the culprit?," Applied Economics Letters, Taylor & Francis Journals, vol. 11(2), pages 81-86.
    9. Mynhardt, H. R. & Plastun, Alex & Makarenko, Inna, 2014. "Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009," MPRA Paper 58942, University Library of Munich, Germany.
    10. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    11. 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.
    12. William R. Morgan, 2023. "Finance Must Be Defended: Cybernetics, Neoliberalism and Environmental, Social, and Governance (ESG)," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    13. Jael, Paul, 2015. "Socialist Calculation and Market Socialism," MPRA Paper 64255, University Library of Munich, Germany.
    14. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    15. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    16. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    17. Anders Johansson, 2009. "An analysis of dynamic risk in the Greater China equity markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 7(3), pages 299-320.
    18. Zhang, Wei-Guo & Li, Zhe & Liu, Yong-Jun, 2018. "Analytical pricing of geometric Asian power options on an underlying driven by a mixed fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 402-418.
    19. Przemyslaw Zbierowski, 2015. "Positive Entrepreneurship: Antecedents and Outcomes of Entrepreneurship within Positive Organizational Scholarship (Przedsiebiorczosc pozytywna – przyczyny i rezultaty przedsiebiorczosci z zakresu poz," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 13(56), pages 38-54.
    20. Cornelis A. Los, 2004. "Nonparametric Efficiency Testing of Asian Stock Markets Using Weekly Data," Finance 0409033, University Library of Munich, Germany.

    More about this item

    Keywords

    Tunisian; finance; market;
    All these keywords.

    Statistics

    Access and download statistics

    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:rfa:bmsjnl:v:3:y:2017:i:2:p:61-77. 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: Redfame publishing (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.