Analyzing comovements and connectedness is critical for providing significant implications
for crypto-portfolio risk management. However, most existing research focuses on the lower …

Academic research relies heavily on exogenous drivers to improve the forecasting accuracy
of Bitcoin volatility. The present study provides additional insight into the role of both …

This paper takes part in the ongoing debate on the newly emerging field of financial
technology by systematically reviewing 164 articles on cryptocurrency volatility during the …

Bitcoin prices are highly volatile and have extreme upper tails of the return distributions. One
important component of Bitcoin price jumps is that it does not follow a normal distribution …

Using 1-min data of nine cryptocurrency prices, spanning the period 2017 to 2021, the
analysis extends Hasan et al., 2021, Ahmed and Al Mafrachi, 2021 papers that explore the …

This study attempts to explore the macroeconomic development factors that determine
countries' decisions to implement CBDCs. The study uses data regarding CBDC adoption …

Given the volatile nature of cryptocurrencies, accurately forecasting cryptocurrency volatility
and understanding its determinants are crucial. This paper applies machine learning (ML) …

We introduce the accelerating generalized autoregressive score (aGAS) technique into the
Gaussian-Cauchy mixture model and propose a novel time-varying mixture (TVM)-aGAS …

Cryptocurrencies play a pivotal role in the financial market. Given this, we perform the
asymmetric multifractal cross-correlation analysis to examine the weak form of the Efficient …

This study uses high-frequency (1-min) price data to examine the connectedness among the
leading cryptocurrencies (ie Bitcoin, Ethereum, Binance, Cardano, Litecoin, and Ripple) at …