We analyze the correlation between different assets in the cryptocurrency market throughout different phases, specifically bearish and bullish periods. Taking advantage of a fine-grained dataset comprising 34 historical cryptocurrency price time series collected tick-by-tick on the HitBTC exchange, we observe the changes in interactions among these cryptocurrencies from two aspects: time and level of granularity. Moreover, the investment decisions of investors during turbulent times caused by the COVID-19 pandemic are assessed by looking at the cryptocurrency community structure using various community detection algorithms. We found that finer-grain time series describes clearer the correlations between cryptocurrencies. Notably, a noise an...
Cryptocurrencies, popularly for their underlying technology and exponential growth in numbers, also ...
The aim of this study is to evaluate the efficiency of integrating cryptocurrencies in a diversified...
Utilizing the generalized spillover index developed by Diebold and Yilmaz (2009, 2012), we investiga...
We analyze the correlation between different assets in the cryptocurrency market throughout differe...
In this study the cross-correlations between the cryptocurrency market represented by the two most l...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
Literature suggests assets become more correlated during economic downturns. The current COVID-19 cr...
Being archetypal complex systems, financial markets exhibit rich set of dynamics in their interactio...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
This research examines the behaviour of cryptocurrencies and stock markets during the COVID-19 pande...
This paper features an analysis of cryptocurrencies and the impact of the COVID-19 pandemic on their...
Cryptocurrencies have gained substantial public interest in recent years. Cryptocurrencies are also ...
Cryptoassets have experienced dramatic volatility in their prices, especially during the COVID-19 pa...
Cryptocurrencies are gradually establishing themselves as a new class of assets with unique features...
We analyze the extent of comovement between daily price returns of nine major cryptocurrencies durin...
Cryptocurrencies, popularly for their underlying technology and exponential growth in numbers, also ...
The aim of this study is to evaluate the efficiency of integrating cryptocurrencies in a diversified...
Utilizing the generalized spillover index developed by Diebold and Yilmaz (2009, 2012), we investiga...
We analyze the correlation between different assets in the cryptocurrency market throughout differe...
In this study the cross-correlations between the cryptocurrency market represented by the two most l...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
Literature suggests assets become more correlated during economic downturns. The current COVID-19 cr...
Being archetypal complex systems, financial markets exhibit rich set of dynamics in their interactio...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
This research examines the behaviour of cryptocurrencies and stock markets during the COVID-19 pande...
This paper features an analysis of cryptocurrencies and the impact of the COVID-19 pandemic on their...
Cryptocurrencies have gained substantial public interest in recent years. Cryptocurrencies are also ...
Cryptoassets have experienced dramatic volatility in their prices, especially during the COVID-19 pa...
Cryptocurrencies are gradually establishing themselves as a new class of assets with unique features...
We analyze the extent of comovement between daily price returns of nine major cryptocurrencies durin...
Cryptocurrencies, popularly for their underlying technology and exponential growth in numbers, also ...
The aim of this study is to evaluate the efficiency of integrating cryptocurrencies in a diversified...
Utilizing the generalized spillover index developed by Diebold and Yilmaz (2009, 2012), we investiga...