This study provides an empirical analysis on the main univariate and multivariate stylized facts iin return series of the two of the largest cryptocurrencies, namely Ethereum and Bitcoin. A Markov- Switching Vector AutoRegression model is considered to further explore the dynamic relationships between cryptocurrencies and other financial assets. We estimate the presence of volatility clustering, a rapid decay of the autocorrelation function, an excess of kurtosis and multivariate little cross-correlation across the series, except for contemporaneous returns. The analysis covers the pandemic period and sheds lights on the behaviour of cryptocurrencies under unexpected extreme events.
On stylized facts of cryptocurrencies returns and their relationship with other assets, with a focus on the impact of COVID-19 / Cremaschini, Alessandro; Punzo, Antonio; Martellucci, Eliano; Maruotti, Antonello. - In: APPLIED ECONOMICS. - ISSN 1466-4283. - (2022). [10.1080/00036846.2022.2117777]
On stylized facts of cryptocurrencies returns and their relationship with other assets, with a focus on the impact of COVID-19
Alessandro CremaschiniPrimo
;Antonello Maruotti
Secondo
2022
Abstract
This study provides an empirical analysis on the main univariate and multivariate stylized facts iin return series of the two of the largest cryptocurrencies, namely Ethereum and Bitcoin. A Markov- Switching Vector AutoRegression model is considered to further explore the dynamic relationships between cryptocurrencies and other financial assets. We estimate the presence of volatility clustering, a rapid decay of the autocorrelation function, an excess of kurtosis and multivariate little cross-correlation across the series, except for contemporaneous returns. The analysis covers the pandemic period and sheds lights on the behaviour of cryptocurrencies under unexpected extreme events.File | Dimensione | Formato | |
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