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High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets

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  • Omane-Adjepong, Maurice
  • Alagidede, Imhotep Paul

Abstract

Inspired by the insurgence of the decade-old cryptocurrency market and its gradual acceptance into mainstream finance, this paper examines the evolving dynamic characteristics of the new currencies, in the midst of diverse emerging assets of the BRICS. We test for chaos in the time and scale return samples using LLE estimations. Our results accept (reject) chaotic structure for almost all the markets at the weekly (full and intraweek) data samples, and further found no copious disparity amongst the dynamic structure of the markets, contrary to the widely reported weak connectedness and somehow isolated cryptocurrencies from other financial assets. The findings hold implications for asset return forecasting, investment risk and regulatory policy.

Suggested Citation

  • Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2020. "High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    • Handle: RePEc:eee:chsofr:v:132:y:2020:i:c:s096007791930520x
    DOI: 10.1016/j.chaos.2019.109563
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    1. Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2019. "Are BRICS exchange rates chaotic?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(13), pages 1104-1110, July.
    2. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    3. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    4. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    5. Garnier, Josselin & Solna, Knut, 2019. "Chaos and order in the bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 708-721.
    6. Houda Litimi & Ahmed Bensaida & Lotfi Belkacem & Oussama Abdallah, 2019. "Chaotic behavior in financial market volatility," Post-Print hal-02869485, HAL.
    7. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Exploring disorder and complexity in the cryptocurrency space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 548-556.
    8. Aslanidis, Nektarios & Bariviera, Aurelio F. & Martínez-Ibañez, Oscar, 2019. "An analysis of cryptocurrencies conditional cross correlations," Finance Research Letters, Elsevier, vol. 31(C), pages 130-137.
    9. Josselin Garnier & Knut Solna, 2018. "Chaos and Order in the Bitcoin Market," Papers 1809.08403, arXiv.org, revised Apr 2019.
    10. Timo Teräsvirta & Chien‐Fu Lin & Clive W. J. Granger, 1993. "Power Of The Neural Network Linearity Test," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(2), pages 209-220, March.
    11. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
    12. Simone Giannerini & Esfandiar Maasoumi & Estela Bee Dagum, 2015. "Entropy testing for nonlinear serial dependence in time series," Biometrika, Biometrika Trust, vol. 102(3), pages 661-675.
    13. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    14. Merediz-Solà, Ignasi & Bariviera, Aurelio F., 2019. "A bibliometric analysis of bitcoin scientific production," Research in International Business and Finance, Elsevier, vol. 50(C), pages 294-305.
    15. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    16. Jeffrey Chu & Saralees Nadarajah & Stephen Chan, 2015. "Statistical Analysis of the Exchange Rate of Bitcoin," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-27, July.
    17. Lahmiri, Salim & Bekiros, Stelios, 2019. "Cryptocurrency forecasting with deep learning chaotic neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 118(C), pages 35-40.
    18. 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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