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Chaos in G7 stock markets using over one century of data: A note

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  • Tiwari, Aviral Kumar
  • Gupta, Rangan

Abstract

In our study, we tested for chaos in the historical daily and monthly datasets spanning over one century of stock returns for G7 countries. Applying the 0–1 test proposed by Gottwald and Melbourne (2005) and the recent test developed by BenSaïda and Litimi (2013), which is powerful in detecting chaotic dynamics, we found that (a) it is better to denoise the data before testing for chaos and (b), in general, chaos is observed for all countries, using both tests, when we denoised the data.

Suggested Citation

  • Tiwari, Aviral Kumar & Gupta, Rangan, 2019. "Chaos in G7 stock markets using over one century of data: A note," Research in International Business and Finance, Elsevier, vol. 47(C), pages 304-310.
  • Handle: RePEc:eee:riibaf:v:47:y:2019:i:c:p:304-310
    DOI: 10.1016/j.ribaf.2018.08.005
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    References listed on IDEAS

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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.
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    Cited by:

    1. Baogui Xin & Wei Peng & Yekyung Kwon, 2019. "A fractional-order difference Cournot duopoly game with long memory," Papers 1903.04305, arXiv.org.

    More about this item

    Keywords

    Chaos; G7 countries; Stock returns;

    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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