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Reprint of: 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.

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  • Tiwari, Aviral Kumar & Gupta, Rangan, 2019. "Reprint of: Chaos in G7 stock markets using over one century of data: A note," Research in International Business and Finance, Elsevier, vol. 49(C), pages 315-321.
    • Handle: RePEc:eee:riibaf:v:49:y:2019:i:c:p:315-321
    DOI: 10.1016/j.ribaf.2019.05.002
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    References listed on IDEAS

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    1. Shapour Mohammadi & Ahmad Pouyanfar, 2011. "Behaviour of stock markets' memories," Applied Financial Economics, Taylor & Francis Journals, vol. 21(3), pages 183-194.
    2. Mishra, Ritesh Kumar & Sehgal, Sanjay & Bhanumurthy, N.R., 2011. "A search for long-range dependence and chaotic structure in Indian stock market," Review of Financial Economics, Elsevier, vol. 20(2), pages 96-104, May.
    3. 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.
    4. 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:

    1. Hamdi, Besma & Aloui, Mouna & Alqahtani, Faisal & Tiwari, Aviral, 2019. "Relationship between the oil price volatility and sectoral stock markets in oil-exporting economies: Evidence from wavelet nonlinear denoised based quantile and Granger-causality analysis," Energy Economics, Elsevier, vol. 80(C), pages 536-552.
    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. Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
    4. 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.
    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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