In this study, we examine the asymmetric efficiency of cryptocurrencies using 1-hour data of Bitcoin, Ethereum, Litecoin, and Ripple. In doing so, we utilize the asymmetric multifractal detrended fluctuation analysis (MF-DFA). We find significant asymmetric multifractality in the price of cryptocurrencies and that upward trends exhibit stronger multifractality than downward trends. Using the time-varying deficiency measure, we show that the COVID-19 outbreak adversely affected the efficiency of the four cryptocurrencies, given a substantial increase in the levels of inefficiency during the COVID-19 period. Bitcoin and Ethereum are the hardest hit, and at the same time, these two largest cryptocurrencies recovered faster at the end of March ...
The present study is on the five cryptocurrency daily mean return time series linearity dynamics dur...
Cryptoassets have experienced dramatic volatility in their prices, especially during the COVID-19 pa...
We investigate any similarity and dependence based on the full distributions of cryptocurrency asset...
This study investigates asymmetric multifractality and market efficiency of the major cryptocurrenci...
This article investigates the dynamical complexity and fractal characteristics changes of the Bitcoi...
Abstract This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the cor...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
This study investigates the volatility of daily Bitcoin returns and multifractal properties of the B...
First published online: September 2020We explore the evolution of the informational efficiency in 45...
Motivated by the lack of research on price efficiency dynamics of green bonds and the impact of the ...
This paper compares the degree of cryptocurrency market efficiency during the pre- and post COVID-19...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
We employ multifractal detrended fluctuation analysis (MF-DFA) to provide the first look at the effi...
In this paper, we study the long memory behavior of Bitcoin, Litecoin, Ethereum, Ripple, Monero, and...
This research analyzes asymmetric volatility and multifractality in four representative cryptocurren...
The present study is on the five cryptocurrency daily mean return time series linearity dynamics dur...
Cryptoassets have experienced dramatic volatility in their prices, especially during the COVID-19 pa...
We investigate any similarity and dependence based on the full distributions of cryptocurrency asset...
This study investigates asymmetric multifractality and market efficiency of the major cryptocurrenci...
This article investigates the dynamical complexity and fractal characteristics changes of the Bitcoi...
Abstract This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the cor...
This paper introduces new methods for analysing the extreme and erratic behaviour of time series to ...
This study investigates the volatility of daily Bitcoin returns and multifractal properties of the B...
First published online: September 2020We explore the evolution of the informational efficiency in 45...
Motivated by the lack of research on price efficiency dynamics of green bonds and the impact of the ...
This paper compares the degree of cryptocurrency market efficiency during the pre- and post COVID-19...
This paper investigates the time-varying co-movements in cryptocurrency market, employing a Dynamic ...
We employ multifractal detrended fluctuation analysis (MF-DFA) to provide the first look at the effi...
In this paper, we study the long memory behavior of Bitcoin, Litecoin, Ethereum, Ripple, Monero, and...
This research analyzes asymmetric volatility and multifractality in four representative cryptocurren...
The present study is on the five cryptocurrency daily mean return time series linearity dynamics dur...
Cryptoassets have experienced dramatic volatility in their prices, especially during the COVID-19 pa...
We investigate any similarity and dependence based on the full distributions of cryptocurrency asset...