Artificial Intelligence Applied to Stock Market Trading: A Review

The application of Artificial Intelligence (AI) to financial investment is a research area that has attracted extensive research attention since the 1990s, when there was an accelerated technological development and popularization of the personal computer. Since then, countless approaches have been proposed to deal with the problem of price prediction in the stock market. This paper presents a systematic review of the literature on Artificial Intelligence applied to investments in the stock market based on a sample of 2326 papers from the Scopus website between 1995 and 2019. These papers were divided into four categories: portfolio optimization, stock market prediction using AI, financial sentiment analysis, and combinations involving two or more approaches. For each category, the initial introductory research to its state-of-the-art applications are described. In addition, an overview of the review leads to the conclusion that this research area is gaining continuous attention and the literature is becoming increasingly specific and thorough.

Automated summary

The application of Artificial Intelligence in financial investment has attracted extensive research attention since the 1990s, and the literature is increasingly becoming more specific and thorough. The reviewed papers on AI in investments in the stock market were categorized into four main areas, showing a development path from initial research to state-of-the-art applications over time.