Volatility Estimation for Bitcoin: A Brazilian Market Evidence / Estimação de Volatilidade do Bitcoin: uma evidência do mercado brasileiro
We revisit volatility throught GARCH models comparison and a Markov-Switching model appli- cation around Bitcoin Brazilian data. Besides exploring the optimal conditional heteroskedasticity model with regards to goodness-of-fit to Bitcoin price data, we also test the regime change between 2011 and 2...
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Brasil |
| Recursos: | Universidade do Estado do Rio de Janeiro (UERJ) |
| Repositorio: | Physis (Online) |
| Idioma: | portugués |
| OAI Identifier: | oai:ojs2.ojs.brazilianjournals.com.br:article/23879 |
| Acesso em linha: | https://ojs.brazilianjournals.com.br/ojs/index.php/BJB/article/view/23879 |
| Access Level: | acceso abierto |
| Palavra-chave: | Bitcoin Volatility GARCH Switching Heteroskedasticity |
| Resumo: | We revisit volatility throught GARCH models comparison and a Markov-Switching model appli- cation around Bitcoin Brazilian data. Besides exploring the optimal conditional heteroskedasticity model with regards to goodness-of-fit to Bitcoin price data, we also test the regime change between 2011 and 2018 for Brazilian market. Finally, it is found that the best conditional heteroskedasticity model is the AR-APARCH and is proved the predominance of Low Regime for Bitcoin Brazilian daily return, even in periods of high volume transactions and price levels. |
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