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Chaos in G7 Stock Markets using Over One Century of Data: A Note

Author

Listed:
  • Aviral Kumar Tiwari

    (Center for Energy and Sustainable Development (CESD), Montpellier Business School, Montpellier, France)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, South Africa)

  • Stelios Bekiros

    (Department of Economics, European University Institute, Florence, Italy)

Abstract

In this paper we test for chaos on historical daily and monthly datasets stock returns for G7 countries spanning over one century. Applying the 0-1 test proposed by Gottwald and Melbourne (2005) and the recent test developed by BenSaïda (2012), which is powerful in detecting chaotic dynamics, we find that: (a) It is better to denoise the data before testing for chaos; (b) In general, chaos is observed for all countries when we denoise the data based on both tests, and; (c) Strong evidence of chaotic behavior is observed in Canada, France and the UK.

Suggested Citation

  • Aviral Kumar Tiwari & Rangan Gupta & Stelios Bekiros, 2016. "Chaos in G7 Stock Markets using Over One Century of Data: A Note," Working Papers 201678, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201678
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    1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    2. Webel, Karsten, 2012. "Chaos in German stock returns — New evidence from the 0–1 test," Economics Letters, Elsevier, vol. 115(3), pages 487-489.
    3. 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.
    4. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
    5. Shapour Mohammadi & Ahmad Pouyanfar, 2011. "Behaviour of stock markets' memories," Applied Financial Economics, Taylor & Francis Journals, vol. 21(3), pages 183-194.
    6. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    7. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    8. Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
    9. Anagnostidis, Panagiotis & Emmanouilides, Christos J., 2015. "Nonlinearity in high-frequency stock returns: Evidence from the Athens Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 473-487.
    10. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
    11. BenSaïda, Ahmed & Litimi, Houda, 2013. "High level chaos in the exchange and index markets," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 90-95.
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    Cited by:

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    2. Alexeeva, Tatyana A. & Barnett, William A. & Kuznetsov, Nikolay V. & Mokaev, Timur N., 2020. "Dynamics of the Shapovalov mid-size firm model," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    3. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.
    4. Baogui Xin & Wei Peng & Yekyung Kwon, 2019. "A fractional-order difference Cournot duopoly game with long memory," Papers 1903.04305, arXiv.org.
    5. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.

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    More about this item

    Keywords

    Chaos; G7 countries; stock returns;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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