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Bitcoin and market-(in)efficiency: a systematic time series approach

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Listed:
  • Nils Bundi

    (Stevens Institute of Technology)

  • Marc Wildi

    (Zurich University of Applied Sciences)

Abstract

Recently, cryptocurrencies have received substantial attention by investors given their innovative features, simplicity and transparency. We here analyze the increasingly popular Bitcoin and verify pertinence of the efficient market hypothesis. Recent research suggests that Bitcoin markets, while inefficient in their early days, transitioned into efficient markets recently. We challenge this claim by proposing simple trading strategies based on moving average filters, on classic time series models as well as on non-linear neural nets. Our findings suggest that trading performances of our designs are significantly positive; moreover, linear and non-linear approaches perform similarly except at singular time periods of the Bitcoin; finally, our results suggest that markets are becoming less rather than more efficient towards the sample end of the data.

Suggested Citation

  • Nils Bundi & Marc Wildi, 2019. "Bitcoin and market-(in)efficiency: a systematic time series approach," Digital Finance, Springer, vol. 1(1), pages 47-65, November.
    • Handle: RePEc:spr:digfin:v:1:y:2019:i:1:d:10.1007_s42521-019-00004-z
    DOI: 10.1007/s42521-019-00004-z
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    References listed on IDEAS

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    Cited by:

    1. Jörg Osterrieder & Andrea Barletta, 2019. "Editorial on the Special Issue on Cryptocurrencies," Digital Finance, Springer, vol. 1(1), pages 1-4, November.
    2. Marc Wildi & Branka Hadji Misheva, 2022. "A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection," Papers 2212.02906, arXiv.org.
    3. Carol Alexander & Jaehyuk Choi & Heungju Park & Sungbin Sohn, 2020. "BitMEX bitcoin derivatives: Price discovery, informational efficiency, and hedging effectiveness," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(1), pages 23-43, January.
    4. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).

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