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Bitcoin's return behaviour: What do We know so far?

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  • Fajardo, José

Abstract

In this paper we study the daily return behavior of Bitcoin digital currency. We propose the use of generalized hyperbolic distributions (GH) to model Bitcoin's return. Our, results show that GH is a very good candidate to model this return.

Suggested Citation

  • Fajardo, José, 2019. "Bitcoin's return behaviour: What do We know so far?," MPRA Paper 93353, University Library of Munich, Germany, revised 16 Apr 2019.
    • Handle: RePEc:pra:mprapa:93353
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    File URL: https://mpra.ub.uni-muenchen.de/93353/1/MPRA_paper_93353.pdf
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    References listed on IDEAS

    as
    1. Fajardo, José & Farias, Aquiles, 2004. "Generalized Hyperbolic Distributions and Brazilian Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 24(2), November.
    2. Marc Gronwald, 2014. "The Economics of Bitcoins - Market Characteristics and Price Jumps," CESifo Working Paper Series 5121, CESifo.
    3. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    4. Olivier Scaillet & Adrien Treccani & Christopher Trevisan, 2020. "High-Frequency Jump Analysis of the Bitcoin Market," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 209-232.
    5. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    6. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    7. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
    8. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    9. Farias, A. R. & Ornelas, J. R. H & Fajardo, J., 2004. "Goodness-of-Fit Test focuses on Conditional Value at Risk:An Empirical Analysis of Exchange Rates," Finance Lab Working Papers flwp_70, Finance Lab, Insper Instituto de Ensino e Pesquisa.
    10. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
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    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Jumps; Generalized Hyperbolic distributions.;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G0 - Financial Economics - - General

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