In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-tradable crypto assets using high-frequency data for the period from January 2019 to December 2020. We apply the Diagonal-BEKK model to data from the pre-COVID and COVID-19 periods, and identify significant changes in patterns of co-movements and correlations during the pandemic period. We also employ the Minimum Spanning Tree (MST) and Planar Maximally Filtered Graph (PMFG) methods to study the changes of the crypto asset network structure after the COVID-19 outbreak. While the influential role of Bitcoin in the digital asset ecosystem has been confirmed, our novel findings reveal that due to recent developments in the blockchain ecosystem, c...
Abstract This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the cor...
In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of r...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-t...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
Master of Science in Finance and Banking. UPF Barcelona School of Management. Curs 2020-2021José B. ...
We use a data-driven methodology, namely the directed acyclic graph, to uncover the contemporaneous ...
Literature suggests assets become more correlated during economic downturns. The current COVID-19 cr...
We investigate any similarity and dependence based on the full distributions of cryptocurrency asset...
In this paper, we attempt to analyze the dynamic interplay between Bitcoin, social media, and the Co...
This paper investigates the relationship between the COVID-19 crisis and the two leading cryptocurre...
Cryptocurrencies are relatively new and innovative financial assets. They are a topic of interest to...
We analyze the correlation between different assets in the cryptocurrency market throughout differen...
This paper features an analysis of cryptocurrencies and the impact of the COVID-19 pandemic on their...
In this paper, we study the long memory behavior of the hourly cryptocurrency returns during the COV...
Abstract This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the cor...
In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of r...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-t...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
Master of Science in Finance and Banking. UPF Barcelona School of Management. Curs 2020-2021José B. ...
We use a data-driven methodology, namely the directed acyclic graph, to uncover the contemporaneous ...
Literature suggests assets become more correlated during economic downturns. The current COVID-19 cr...
We investigate any similarity and dependence based on the full distributions of cryptocurrency asset...
In this paper, we attempt to analyze the dynamic interplay between Bitcoin, social media, and the Co...
This paper investigates the relationship between the COVID-19 crisis and the two leading cryptocurre...
Cryptocurrencies are relatively new and innovative financial assets. They are a topic of interest to...
We analyze the correlation between different assets in the cryptocurrency market throughout differen...
This paper features an analysis of cryptocurrencies and the impact of the COVID-19 pandemic on their...
In this paper, we study the long memory behavior of the hourly cryptocurrency returns during the COV...
Abstract This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the cor...
In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of r...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...