A systematic review: an analysis of stock market prediction

Stock market prediction is a complex and dynamic field that has attracted significant attention from researchers and practitioners seeking to enhance investment decision-making and maximize returns. The goal of this systematic literature review is to give a thorough examination of existing studies on stock market prediction strategies. By synthesizing a wide range of research articles, this review examines the methodologies employed, data sources utilized, predictive models developed, and evaluation metrics applied in the context of stock market prediction. The findings highlight the strengths and limitations of different approaches, such as statistical models, machine learning algorithms, and hybrid techniques. Furthermore, this review identifies research gaps and suggests future directions for improving stock market prediction accuracy. The insights gained from this systematic literature review contribute to understanding the current state of stock market prediction research, facilitate knowledge exchange among researchers, and offer valuable guidance for further advancements in this field.