Advancements in AI for Predicting Price Movements: An In-Depth Literature Survey

Financial market prediction is a fascinating subject because of its potential for financial gain, but it is also highly complex because of the multitude of interrelated factors that impact prices. The ability to accurately predict price movements is crucial for portfolio managers, who typically aim to buy assets that are expected to increase in value and sell assets that are expected to decline. Artificial intelligence (AI) techniques, such as machine learning, symbolic AI, natural language processing (NLP), and expert systems, can assist practitioners in predicting price movements. It is, however, challenging to cover and find all possible techniques comprehensively. This article aims to shed light on the current state of AI techniques for price movement predictions in the financial market by examining the existing literature from 2019 to 2022. To analyze the current trends, a total of 31 articles have been reviewed, which were obtained from the Scopus scientific database. The primary contribution of this work is to offer researchers and financial analysts a structured and systematic review of applications of AI in financial markets forecasting. It categorizes research into three areas, ranks models based on evaluation, and covers diverse financial instruments.