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Estimación de la distribución multivariada de los rendimientos de los tipos de cambio contra el dólar de las criptomonedas Bitcoin, Ripple y Ether

Author

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  • Beatriz Mota Aragón

    (Universidad Autónoma Metropolitana, México)

  • José Antonio Núñez Mora

    (Tecnológico de Monterrey, México)

Abstract

En este artículo se estima la distribución multivariada para analizar la dependencia del Bitcoin (BTC), Ripple (XRP) y Ether (ETH). Se utiliza la familia Hiperbólica Generalizada de distribuciones (GH) y en particular la distribución Varianza Gamma. El procedimiento para la estimación de los parámetros de la GH es a través del algoritmo EM (Expectation-Maximization). Los resultados muestran que existe una dependencia positiva entre los tres tipos de cambio respecto del dólar americano y se estima una distribución Varianza-Gamma de dimensión tres. Esta distribución es muy flexible para el ajuste de series de los rendimientos con leptocurtosis y sesgo. Esta información se considera importante para los inversionistas que conforman sus portafolios de una manera eficiente.

Suggested Citation

  • Beatriz Mota Aragón & José Antonio Núñez Mora, 2019. "Estimación de la distribución multivariada de los rendimientos de los tipos de cambio contra el dólar de las criptomonedas Bitcoin, Ripple y Ether," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(3), pages 447-457, Julio - S.
    • Handle: RePEc:imx:journl:v:14:y:2019:i:3:p:447-457
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    References listed on IDEAS

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    1. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    2. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    3. Ratner, Mitchell & Chiu, Chih-Chieh (Jason), 2013. "Hedging stock sector risk with credit default swaps," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 18-25.
    4. Michael McAssey, 2013. "An empirical goodness-of-fit test for multivariate distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(5), pages 1120-1131.
    5. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    6. Pradipta Kumar SAHOO, 2017. "Bitcoin as digital money: Its growth and future sustainability," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(613), W), pages 53-64, Winter.
    7. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    8. Neil Gandal & Hanna Halaburda, 2016. "Can We Predict the Winner in a Market with Network Effects? Competition in Cryptocurrency Market," Games, MDPI, vol. 7(3), pages 1-21, July.
    9. David Garcia & Claudio Tessone & Pavlin Mavrodiev & Nicolas Perony, "undated". "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Working Papers ETH-RC-14-001, ETH Zurich, Chair of Systems Design.
    10. Dwyer, Gerald P., 2015. "The economics of Bitcoin and similar private digital currencies," Journal of Financial Stability, Elsevier, vol. 17(C), pages 81-91.
    11. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    12. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    13. Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
    14. Demir, Ender & Gozgor, Giray, 2018. "Does economic policy uncertainty affect Tourism?," Annals of Tourism Research, Elsevier, vol. 69(C), pages 15-17.
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    More about this item

    Keywords

    leptokurtosis; skewness; Variance-Gamma; Multivariate;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

    Statistics

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