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Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin

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  • Tong, Zhongwen
  • Chen, Zhanbo
  • Zhu, Chen

Abstract

The price fluctuation of cryptocurrencies represented by Bitcoin has nonlinear structure characteristics. We select the Bitcoin closing price data from 2013 to 2021, and use GARCH (1,1)-GED to fit the volatility series. We confirm that Bitcoin price Fluctuation has nonlinear dynamics through BDS test, Hurst exponent, correlation dimension test and Lyapunov exponent. We find that the price fluctuation of cryptocurrency does not obey the random walk, and its fluctuation is positively correlated with time. Bullish information and bearish information have basically the same impact on cryptocurrency fluctuations. Cryptocurrency price fluctuations have cyclical trends and inherent long-term unpredictability, as well as certain fractal and chaos characteristics. ARCH effect and long memory characteristics of cryptocurrency return series show that cryptocurrency price fluctuations are Clustering and persistence. These two characteristics constitute the nonlinear dynamic mechanism of Bitcoin price fluctuation. Overall, our study has important implications for investors and regulators within cryptocurrency markets.

Suggested Citation

  • Tong, Zhongwen & Chen, Zhanbo & Zhu, Chen, 2022. "Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin," Finance Research Letters, Elsevier, vol. 47(PB).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pb:s1544612322001155
    DOI: 10.1016/j.frl.2022.102803
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    References listed on IDEAS

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    Cited by:

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    2. Olanipekun, Ifedolapo Olabisi & Ozkan, Oktay & Olasehinde-Williams, Godwin, 2023. "Is renewable energy use lowering resource-related uncertainties?," Energy, Elsevier, vol. 271(C).

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    More about this item

    Keywords

    Cryptocurrency; Nonlinear dynamics analysis; BDS test; Long memory; Price fluctuations;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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