… continue to be one of the most challenging research areas due to dynamic, … This study
explains the systematics of machine learning-based approaches for stock market prediction based …

… review, we investigate machine learning techniques that are applied for stock market …
Moreover, through a short bibliographic analysis, this study also aimed to gain an understanding of …

… , in this study, we develop a novel sentiment index to predict the stock trends based on the
… algorithms are widely used to mine historical data and predict stock market sentiment. For …

… The stock market forecasting system is to increase accuracy. In this study to analyze a novel
approach to improve the prediction of the results of stock, it means we will combine two or …

… a concise review of stock markets and taxonomy of stock market prediction methods. … survey
of supervised and unsupervised machine learning methods applied in stock market analysis …

… this paper is to review different machine learning models to predict the stock market’s movement.
… In this paper, Section II describe the types of machine learning. section III describe the …

… This study surveys more than 150 related articles on applying machine learning to financial
market forecasting. Based on a comprehensive literature review, we build a table across …

… developed for financial market applications. Section 5 provides a description of studies …
, the surveyed studies conducted and reported in this article show that deep learning-based …

… research articles that were relevant to stock market forecasting that used machine learning
and deep learning … This study aimed to consider recent research articles (20182021) to …

… other evolutionary techniques for stock market forecasting. This paper presents an up-to-date
survey of existing literature on stock market forecasting based on computational intelligent …