Fajardo, José (2019): Bitcoin's return behaviour: What do We know so far?
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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.
Item Type: | MPRA Paper |
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Original Title: | Bitcoin's return behaviour: What do We know so far? |
English Title: | Bitcoin's return behaviour: What do We know so far? |
Language: | English |
Keywords: | Bitcoin, Cryptocurrency, Jumps, Generalized Hyperbolic distributions. |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics G - Financial Economics > G0 - General |
Item ID: | 93353 |
Depositing User: | José S Fajardo |
Date Deposited: | 25 Apr 2019 17:50 |
Last Modified: | 29 Sep 2019 01:05 |
References: | \bibitem{Bal} Balcilar, M., Bouri, E., Gupta, R., Roubaud, D., 2017. Can volume predict bitcoin returns and volatility? a quantiles-based approach. Economic Modelling 64, 74–81. \bibitem{barn1977} Barndorff-Nielsen, O., 1977. Exponentially Decreasing Distributions for the Logarithm of Particle Size. Proceedings of the Royal Society London A, 353, 401-419. \bibitem{Bar} Bariviera, A. F., 2017. The inefficiency of bitcoin revisited: A dynamic approach. Economics Letters 161, 1–4. \bibitem{Cha} Chaim, P., Laurini, M., 2018. Volatility and return jumps in bitcoin. Economics Letters 173, 158-163. \bibitem{Ebe} Eberlein, E., Prause, K., 2002. The generalized hyperbolic model: financial derivatives and risk measures. Mathematical Finance—Bachelier Congress 2000, 245-267. \bibitem{FFaj} Fajardo, J, Farias, A., 2004. Generalized Hyperbolic Distributions and Brazilian Data. Brazilian Review of Econometrics, 24(2), 1-21. \bibitem{Faj} Fajardo, J., Ornelas, J., Farias, A., 2008. Goodness-of-Fit Test focuses on Conditional Value at Risk: An Empirical Analysis of Exchange Rates. Brazilian Review of Finance, 6(2), 139-155. \bibitem{Gro} Gronwald, M., 2014. The Economics of Bitcoins- Market Characteristics and Price Jumps. Tech. rep. \bibitem{Kat} Katsiampa, P., 2017. Volatility estimation for bitcoin: A comparison of garch models. Economics Letters 158, 3–6. \bibitem{nak} Nakamoto, S., 2008. Bitcoin: A peer-to-peer electronic cash system. www.bitcoin.org. \bibitem{Sca} Scaillet, O., Treccani, A., Trevisan, C., 2017. High-frequency jump analysis of the bitcoin market . \bibitem{tiw} Tiwari A.K., Jana R., Das D., Roubaud D. 2018. Informational efficiency of Bitcoin—An extension Economics Letters, 163, 106-109 \bibitem{Ur} Urquhart, A., 2016. The inefficiency of bitcoin. Economics Letters 148, 80–82. \bibitem{wei} Wei, W. C., 2018. Liquidity and market efficiency in cryptocurrencies. Economics Letters 168, 21–24. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/93353 |