Browsing by Keywords "Cryptocurrency"
Now showing items 1-7 of 7
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Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning
(Elsevier Inc., 2022-05-24)As an emerging asset, cryptocurrencies have attracted more and more attention from investors and researchers in recent years. With the gradual convergence of the investors in cryptocurrency and traditional financial markets, ... -
Correction to: High frequency multiscale relationships among major cryptocurrencies: portfolio management implications
(SpringerOpen, 2021-10-29)This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window ... -
A cryptocurrency incentivized voluntary grid computing platform for DNA read alignment
(Bilkent University, 2019-09)The main computational bottleneck of High Throughput Sequencing (HTS) data analysis is to map the reads to a reference genome, for which clusters are typically used. However, building clusters large enough to handle ... -
High-frequency return and volatility spillovers among cryptocurrencies
(Routledge, 2021-03-22)We examine the high-frequency return and volatility of major cryptocurrencies and reveal that spillovers among them exist. Our analysis shows that return and volatility clustering structures are distinct among different ... -
The impact of blockchain related name changes on corporate performance
(Elsevier, 2020)This paper examines the impact of blockchain and crypto-related name changes on corporate and financial performance of the corporations. We document several pieces of evidence suggesting that companies who partake in such ... -
Investor attention and idiosyncratic risk in cryptocurrency markets
(Routledge, 2021-12-18)We explore the impact of investor attention on idiosyncratic risk in the cryptocurrency markets. Taking the Google Trends Index as the measure of investor attention, we find that investor attention can significantly reduce ... -
Prediction of cryptocurrency returns using machine learning
(Springer, 2021-02)In this study, the predictability of the most liquid twelve cryptocurrencies are analyzed at the daily and minute level frequencies using the machine learning classification algorithms including the support vector machines, ...
