Intricacy of cryptocurrency returns
This paper quantifies the intricacy, i.e., non-linearity and interactions of predictor variables, in explaining cryptocurrency returns. Using data from several thousand cryptocurrencies spanning 2014 to 2022, we observe a notably high level of intricacy.
openaire +3 more sources
Development of a cryptocurrency price prediction model: leveraging GRU and LSTM for Bitcoin, Litecoin and Ethereum. [PDF]
Kaur R+7 more
europepmc +1 more source
Weighted Moving Average of Forecasting Method for Predicting Bitcoin Share Price using High Frequency Data: A Statistical Method in Financial Cryptocurrency Technology [PDF]
Nashirah Abu Bakar, Sofian Rosbi
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An empirical evaluation of fuzzy bidirectional long short-term memory with soft computing based decision-making model for predicting volatility of cryptocurrencies. [PDF]
Ragab M.
europepmc +1 more source
A swarm-optimization based fusion model of sentiment analysis for cryptocurrency price prediction. [PDF]
Tiwari D+5 more
europepmc +1 more source
Graph convolution network for fraud detection in bitcoin transactions. [PDF]
Asiri A, Somasundaram K.
europepmc +1 more source
Cryptocurrency Trading and Associated Mental Health Factors: A Scoping Review. [PDF]
Jain L+5 more
europepmc +1 more source
COMPARATIVE ANALYSIS OF VOLATILITY OF CRYPTOCURRENCIES AND FIAT MONEY
G. O. Krylov+2 more
openalex +2 more sources
The Deficient Role of Latin America in Regulation of Cryptocurrency [PDF]
Juan Emmanuel Delva Benavides+1 more
openalex +1 more source
An assessment of cryptocurrencies as a global commercial determinant of health. [PDF]
Davies N.
europepmc +1 more source