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Artificial Intelligence (AI) approaches have been increasingly used in financial markets as technology advances. In this research paper, we conduct a Systematic Literature Review (SLR) that studies financial trading approaches through AI techniques. It reviews 143 research articles that implemented AI techniques in financial trading markets. Accordingly, it presents several findings and observations after reviewing the papers from the following perspectives: the financial trading market and the asset type, the trading analysis type considered along with the AI technique, and the AI techniques utilized in the trading market, the estimation and performance metrics of the proposed models. The selected research articles were published between 2015 and 2023, and this review addresses four RQs. After analyzing the selected research articles, we observed 8 financial markets used in building predictive models. Moreover, we found that technical analysis is more adopted compared to fundamental analysis. Furthermore, 16% of the selected research articles entirely automate the trading process. In addition, we identified 40 different AI techniques that are used as standalone and hybrid models. Among these techniques, deep learning techniques are the most frequently used in financial trading markets. Building prediction models for financial markets using AI is a promising field of research, and academics have already deployed several machine learning models. As a result of this evaluation, we provide recommendations and guidance to researchers.
Dakalbab et al. (Fri,) studied this question.