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All the frequencies matter in the Bitcoin market: an efficiency analysis

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  • David Vidal-Tomás

Abstract

Most studies in the Bitcoin literature are focused on daily data without considering other options. Therefore, it is necessary to analyse Bitcoin features at different frequencies. In this letter, we examine Bitcoin efficiency from 1 min to weekly data using the generalized Hurst exponent. Our results show that Bitcoin is more efficient over time regardless of the frequency. In particular, we observe that, since 2016, daily data are generally the most efficient frequency while 1 min and weekly data are the most inefficient. These results are relevant for investors and scholars since we detect the most profitable frequencies and underline the relevance of analysing different frequencies than daily data.

Suggested Citation

  • David Vidal-Tomás, 2022. "All the frequencies matter in the Bitcoin market: an efficiency analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 29(3), pages 212-218, February.
    • Handle: RePEc:taf:apeclt:v:29:y:2022:i:3:p:212-218
    DOI: 10.1080/13504851.2020.1861196
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    Cited by:

    1. Hyeonoh Kim & Eojin Yi & Jooyoung Jeon & Taeyoung Park & Kwangwon Ahn, 2024. "After the Split: Market Efficiency of Bitcoin Cash," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 411-427, July.
    2. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).
    3. Antonio Briola & Tomaso Aste, 2022. "Dependency structures in cryptocurrency market from high to low frequency," Papers 2206.03386, arXiv.org, revised Dec 2022.
    4. Ailie Charteris & Conrad Alexander Steyn, 2023. "The Bank of Japan’s exchange traded fund purchases: a help or hindrance to market efficiency?," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 225-240, May.
    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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