[HTML][HTML] Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction

AA Oyedele, AO Ajayi, LO Oyedele, SA Bello… - Expert Systems with …, 2023 - Elsevier
The emergence of cryptocurrencies has drawn significant investment capital in recent years
with an exponential increase in market capitalization and trade volume. However, the …

Forecasting cryptocurrency price using convolutional neural networks with weighted and attentive memory channels

Z Zhang, HN Dai, J Zhou, SK Mondal… - Expert Systems with …, 2021 - Elsevier
After the invention of Bitcoin as well as other blockchain-based peer-to-peer payment
systems, the cryptocurrency market has rapidly gained popularity. Consequently, the …

Exogenous drivers of Bitcoin and Cryptocurrency volatility–A mixed data sampling approach to forecasting

T Walther, T Klein, E Bouri - Journal of International Financial Markets …, 2019 - Elsevier
We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility
of five highly capitalized Cryptocurrencies (Bitcoin, Etherium, Litecoin, Ripple, and Stellar) …

Complexity analysis and forecasting of variations in cryptocurrency trading volume with support vector regression tuned by Bayesian optimization under different …

S Lahmiri, S Bekiros, F Bezzina - Expert Systems with Applications, 2022 - Elsevier
When cryptocurrency markets generate billions of dollars, it becomes interesting to forecast
variation in volume of transactions for better trading and for better management of …

[PDF][PDF] Emergence of Bitcoin as an Investment Alternative: A Systematic Review and Research Agenda.

GD Sharma, M Jain, M Mahendru… - … Journal of Business …, 2019 - researchgate.net
Although Bitcoin has experienced immense popularity and growth since its inception, it has
been essentially ignored by researchers because of its volatile and highly speculative …

Objective and subjective risks of investing into cryptocurrencies

M Angerer, CH Hoffmann, F Neitzert, S Kraus - Finance Research Letters, 2021 - Elsevier
New empirical evidence on cryptocurrencies emerges rapidly, and it is thus necessary to
consolidate the knowledge gained and identify the gaps therein. We provide a focused …

Multi-transformer: A new neural network-based architecture for forecasting S&P volatility

E Ramos-Pérez, PJ Alonso-González… - Mathematics, 2021 - mdpi.com
Events such as the Financial Crisis of 2007–2008 or the COVID-19 pandemic caused
significant losses to banks and insurance entities. They also demonstrated the importance of …

On improving GARCH volatility forecasts for Bitcoin via a meta-learning approach

S Aras - Knowledge-Based Systems, 2021 - Elsevier
Modelling the volatility of Bitcoin, the cryptocurrency with the largest market share, has
recently attracted considerable attention from researchers, practitioners and investors in …

Long memory in the volatility of selected cryptocurrencies: Bitcoin, Ethereum and Ripple

P Kaya Soylu, M Okur, Ö Çatıkkaş… - Journal of Risk and …, 2020 - mdpi.com
This paper examines the volatility of cryptocurrencies, with particular attention to their
potential long memory properties. Using daily data for the three major cryptocurrencies …

Cellular traffic prediction based on an intelligent model

FW Alsaade… - Mobile information …, 2021 - Wiley Online Library
The evolution of cellular technology development has led to explosive growth in cellular
network traffic. Accurate time‐series models to predict cellular mobile traffic have become …