IDEAS home Printed from
   My bibliography  Save this article

Chaotic Structure of the BRIC Countries and Turkey’s Stock Market


  • Samet Günay

    (Department of Banking and Finance, School of Applied Sciences, Istanbul Arel University, Istanbul, Turkey.)


In this study, the parameters of chaos are analyzed for the leading emerging stock markets: Brazil, Russia, India, China, and Turkey (BRIC-T). As chaos has properties such as nonlinearity, sensitivity to initial conditions, and fractality, we performed different methods to identify the existence of the chaos in stock index returns of the BRIC-T countries, using the Brock-Dechert-Scheinkman test, the Largest Lyapunov exponent and the Box-Counting method. Although there is widespread interest in chaos in finance theory, previous studies have neglected the long memory issue in their filtering model of nonlinear behaviors. Due to the fact that the Rescaled Range (R/S) analysis and Smith’s (2005) modified GPH test indicated long memory in the index returns, we filtered the linear structure of the returns using the methods (ARFIMA, FIGARCH, FIEGARCH) which take long memory into account. Though the results have some significant evidence of chaos, the findings are too weak to support the presence of chaos in the stock markets of BRIC-T countries.

Suggested Citation

  • Samet Günay, 2015. "Chaotic Structure of the BRIC Countries and Turkey’s Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 5(2), pages 515-522.
  • Handle: RePEc:eco:journ1:2015-02-24

    Download full text from publisher

    File URL:
    Download Restriction: no

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Guglielmo Maria Caporale, 2005. "The BDS Test as a Test for the Adequacy of a GARCH(1,1) Specification: A Monte Carlo Study," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(2), pages 282-309.
    2. Bajo-Rubio, Oscar & Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1992. "Chaotic behaviour in exchange-rate series : First results for the Peseta--U.S. dollar case," Economics Letters, Elsevier, vol. 39(2), pages 207-211, June.
    3. Abhyankar, A & Copeland, L S & Wong, W, 1997. "Uncovering Nonlinear Structure in Real-Time Stock-Market Indexes: The S&P 500, the DAX, the Nikkei 225, and the FTSE-100," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 1-14, January.
    4. Arjun Chatrath & Bahram Adrangi & Todd Shank, 2001. "Nonlinear Dependence in Gold and Silver Futures: Is it Chaos?," The American Economist, Sage Publications, vol. 45(2), pages 25-32, October.
    5. Brock, W. A., 1986. "Distinguishing random and deterministic systems: Abridged version," Journal of Economic Theory, Elsevier, vol. 40(1), pages 168-195, October.
    6. John Barkoulas & Nickolaos Travlos, 1998. "Chaos in an emerging capital market? The case of the Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 8(3), pages 231-243.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. 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.
    2. Adil Yilmaz & Gazanfer Unal, 2016. "Chaos in Fractionally Integrated Generalized Autoregressive Conditional Heteroskedastic Processes," Papers 1601.08099,, revised Feb 2016.
    3. Gencer, Murat & Unal, Gazanfer, 2016. "Testing Non-Linear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities," MPRA Paper 74115, University Library of Munich, Germany.

    More about this item


    Chaos; Fractals; Largest Lyapunov Exponent; Brock-Dechert-Scheinkman Test; Fractal Dimension;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)


    Access and download statistics


    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:eco:journ1:2015-02-24. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ilhan Ozturk). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.