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1 septembre 2020
- handle: 10670/1.uoiesa
Ce document est lié à :
10.22201/fca.24488410e.2020.2358
info:eu-repo/semantics/openAccess
Mots-clés
Bitcoin volatility MS-GARCH Bayesian estimation C11 C22 G17Citer ce document
Omar Rojas et al., « A Bayesian study of changes in volatility of Bitcoin », Contaduría y administración, ID : 10670/1.uoiesa
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Résumé
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.