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Dynamic characteristic of Bitcoin cryptocurrency in the reconstruction scheme

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  • Alves, P.R.L.

Abstract

The methodology for detecting chaos from a time series is able if stock market indexes or oil prices are the observables. The analysis of volatilities and returns require only a series of historical prices. Routines run in the Maple environment. The conveniences of the symbolic computation are decisive for studies in this line of research. This work extends the domain of application in Econophysics if the observables are prices of cryptocurrencies. The methods include the detection of chaos and randomness. Application of the computational routines provides conclusive results on the underlying dynamics of the Bitcoin market since 18 Jul. 2010 to 06 May 2019. These results include a direct comparison between the Dow Jones stock market and Bitcoin prices.

Suggested Citation

  • Alves, P.R.L., 2020. "Dynamic characteristic of Bitcoin cryptocurrency in the reconstruction scheme," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:chsofr:v:134:y:2020:i:c:s0960077920300941
    DOI: 10.1016/j.chaos.2020.109692
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    References listed on IDEAS

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    Cited by:

    1. Lahmiri, Salim & Bekiros, Stelios, 2020. "The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Alves, P.R.L., 2022. "Quantifying chaos in stock markets before and during COVID-19 pandemic from the phase space reconstruction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 480-499.
    3. Cao, Guangxi & Ling, Meijun, 2022. "Asymmetry and conduction direction of the interdependent structure between cryptocurrency and US dollar, renminbi, and gold markets," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).

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