Advance AI and Machine Learning Approaches for Financial Market Prediction and Risk Management: A Comprehensive Review

Abstract

Stock market is one of the most important sectors of a country's economy. It is challenging to forecast the movements of stock values because they are subject to fluctuations. It is quite challenging to estimate stock market returns with any level of accuracy due to the non-linearity and volatility of the financial stock market. Stock market prediction is the process of making an effort to anticipate the future value of a company's shares or any other financial instrument traded on a financial exchange. Accurately predicting a stock's future price will maximize investor gains. Using a range of Machine Learning techniques and data sets, stock market prediction has long been a prominent field of study. In this paper a comprehensive review on the state-of-the-art methods in Advanced AI Models and Machine Learning Techniques in Financial Market Analysis, Investigating Hybrid and AI-Driven Approaches for Improved Stock Market Predictions, Machine Learning and Deep Learning Techniques for Stock Market Prediction, and Advanced AI and Hybrid Models for Financial Market Prediction is carried out. Future directions has been discussed.