The research purpose of this paper is to obtain an algorithm model with high prediction
accuracy for the price of Bitcoin on the next day through random forest regression and …

We use time and frequency connectedness approaches based on network analysis to
investigate the volatility connectedness among 27 emerging equity markets and seven high …

This study examines the dependence structure and estimates the Value at Risk (V a R) and
risk spillover between cryptocurrencies, oil, and Gold market data. In this paper, we estimate …

Several machine learning techniques and hybrid architectures for predicting bitcoin price
movement have been presented in the past. Our paper proposes a hybrid model …

Cryptoassets have experienced dramatic volatility in their prices, especially during the
COVID-19 pandemic era. This pilot study explores the volatility asymmetry and correlations …

This study examines the volatility of nine leading cryptocurrencies by market capitalization—
Bitcoin, XRP, Ethereum, Bitcoin Cash, Stellar, Litecoin, TRON, Cardano, and IOTA-by using …

This paper reviews copula methods used for economic and finance. Copula allows
researchers to relax the traditional linear model assumptions so that researchers can specify …

The whole world has entered the era of the Vuca. Some traditional methods of problem
analysis begin to fail. Complexity science is needed to study and solve problems from the …

In this study, we predicted the log returns of the top 10 cryptocurrencies based on market
cap, using univariate and multivariate machine learning methods such as recurrent neural …

Employing the standard event study methodology and the OLS market model to examine
how the global pandemic announcement impacted cryptocurrencies, we test the null …