In this literature review, we investigate machine learning techniques that are applied for
stock market prediction. A focus area in this literature review is the stock markets …

Researchers and practitioners have attempted to predict the financial market by analyzing
textual (eg, news articles and social media) and numeric data (eg, hourly stock prices, and …

AI in finance refers to the applications of AI techniques in financial businesses. This area has
attracted attention for decades, with both classic and modern AI techniques applied to …

This study derives its motivation from the current global pandemic, COVID-19, to evaluate
the relevance of health-news trends in the predictability of stock returns. We demonstrate …

Abstract The coronavirus disease (COVID-19) pandemic has already caused enormous
damage to the global economy and various industries worldwide, especially the tourism …

The creation of a predictive system that correctly forecasts future changes of a stock price is
crucial for investment management and algorithmic trading. The use of technical analysis for …

This study examines the impact of live chat on purchase decisions in the context of online
outsourcing platforms. A theoretical research model based on signaling theory is proposed …

With the advent of the Big Data era and the development of machine learning technologies,
predicting stock movements by analyzing news articles, which are unstructured data, has …

A significant correlation between financial news with stock market trends has been explored
extensively. However, very little research has been conducted for stock prediction models …

This study aims to predict the direction of US stock prices by integrating time-varying
effective transfer entropy (ETE) and various machine learning algorithms. At first, we explore …