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Chaos and Predictability in Cryptocurrencies

Author

Listed:
  • Salim Lahmiri

    (Department of Supply Chain and Business Technology Management, John Molson School of Business, Concordia University, Montreal, QC H3H 0A1, Canada
    Chaire Innovation et Économie Numérique, ESCA École de Management, Casablanca 20250, Morocco)

  • Stelios Bekiros

    (Department of Management ‘Valter Cantino’, University of Turin, 10124 Turin, Italy)

Abstract

Background: Lyapunov exponent has been used in many science and engineering problems to quantify chaos in systems and understand their nonlinear dynamics. In financial engineering and forecasting, evaluation of chaos in financial data helps determine whether the data are predictable and if profits can be generated. The purpose of this study is to examine presence of chaos in cryptocurrency markets. Methods: To examine chaos, Lyapunov exponent is computed from a set of 50 cryptocurrencies and statistical one-sided and two-sided Student- t tests are performed to check if on average the computed Lyapunov exponents are equal, less, or larger than zero. Results: The statistical results reveal strong evidence that prices, returns, and trading volume changes are all chaotic; hence, they show nonlinear and deterministic characteristics. Conclusions: Prices, returns, and trading volume changes in cryptocurrencies could be predicted in the short run; for instance, on a daily basis. In this regard, active traders and investors may implement predictive systems to generate daily profits.

Suggested Citation

  • Salim Lahmiri & Stelios Bekiros, 2026. "Chaos and Predictability in Cryptocurrencies," Forecasting, MDPI, vol. 8(3), pages 1-15, June.
    • Handle: RePEc:gam:jforec:v:8:y:2026:i:3:p:48-:d:1965906
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