This review aims to analyze and synthesize the literature produced so far on investor
behavior in the cryptocurrency market. We use VOSviewer 1.6. 17 software to perform a …

This systematic literature review analyses the recent advances of machine learning and
deep learning in finance. The study considers six financial domains: stock markets, portfolio …

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 …

Over the past few years, Bitcoin price prediction has been changed to a big challenge for
investors on cryptocurrencies. In this regard, Neural Networks as a strong structure for …

Predicting price trends of cryptocurrencies is a challenging task due to the highly speculative
cryptocurrency market. Prior studies mainly investigate predictors such as historical trading …

Buildings account for a significant portion of our overall energy usage and associated
greenhouse gas emissions. With the increasing concerns regarding climate change, there …

This study focuses on using the Neural Prophet framework to forecast Bitcoin prices
accurately. By analyzing historical Bitcoin price data, the study aims to capture patterns and …

This article employs machine learning models to predict returns for 3703 cryptocurrencies
for the 2013–2021 period. Based on daily data, we build an equal (capital)-weighted …

The present work applies deep learning and blockchain technology to evaluate and control
the risk of the supply chain finance market, to cope with the diversifications of the financial …

We consider stock price charts as images and use deep learning neural networks (DLNNs)
for image modeling. DLNNs can imitate the work of a technical analyst to predict stock price …