A Bayesian study of changes in volatility of Bitcoin

• Omar Rojas ^[1] ; Semei Coronado
  1. [1] Universidad Panamericana

     Universidad Panamericana

     México

     
• Localización: Contaduría y administración, ISSN 0186-1042, ISSN-e 2448-8410, Vol. 65, Nº. 3, 2020
• Idioma: inglés
• Títulos paralelos:
  • Un estudio Bayesiano de los cambios de volatilidad del Bitcoin
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    Este artículo está enfocado en estudiar un modelo MS-GARCH aplicado al Bitcoin. La estimación bayesiana del modelo muestra que la volatilidad del Bitcoin puede ser modelada utilizando dos estados de volatilidad, alto y bajo. La volatilidad modelada no es estable en el tiempo. Se encontraron veintiocho periodos de alta volatilidad, el periodo de volatilidad más grande ocurrió durante el 2013. Los hallazgos ayudan a explicar qué pasó durante estos periodos de alta volatilidad.

  • English

    This paper is aimed at studying a MS-GARCH model applied to Bitcoin. The Bayesian estimation of the model shows that Bitcoin’s volatility can be modelled using two states of volatility, high and low.

    The modelled volatility is not stable over time. Twenty eight periods of high volatility were found, the largest period of volatility occurred during 2013. The findings help explain what happened during these high volatility periods.

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