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Predictability of bitcoin returns

Author

Listed:
  • Jeremy Eng-Tuck Cheah
  • Di Luo
  • Zhuang Zhang
  • Ming-Chien Sung

Abstract

This paper comprehensively examines the performance of a host of popular variables to predict Bitcoin returns. We show that time-series momentum, economic policy uncertainty, and financial uncertainty outperform other predictors in all in-sample, out-of-sample, and asset allocation tests. Bitcoin returns have no exposure to common stock and bond market factors but rather are affected by Bitcoin-specific and external uncertainty factors.

Suggested Citation

  • Jeremy Eng-Tuck Cheah & Di Luo & Zhuang Zhang & Ming-Chien Sung, 2022. "Predictability of bitcoin returns," The European Journal of Finance, Taylor & Francis Journals, vol. 28(1), pages 66-85, January.
    • Handle: RePEc:taf:eurjfi:v:28:y:2022:i:1:p:66-85
    DOI: 10.1080/1351847X.2020.1835685
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    Citations

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    Cited by:

    1. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    2. Giacomo di Tollo & Joseph Andria & Gianni Filograsso, 2023. "The Predictive Power of Social Media Sentiment: Evidence from Cryptocurrencies and Stock Markets Using NLP and Stochastic ANNs," Mathematics, MDPI, vol. 11(16), pages 1-18, August.
    3. Adam Baybutt, 2024. "Empirical Crypto Asset Pricing," Papers 2405.15716, arXiv.org.
    4. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    5. Shimeng Shi & Jia Zhai & Yingying Wu, 2024. "Informational inefficiency on bitcoin futures," The European Journal of Finance, Taylor & Francis Journals, vol. 30(6), pages 642-667, April.

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