Stock Market Prediction System

Abstract

This review paper examines the recent advancements in stock market prediction using Support Vector Machines (SVM) from 2020 to 2024. We systematically searched and selected 30 relevant studies, focusing on SVM-based models. Our observational study reveals significant improvements in prediction accuracy, with an average accuracy rate of 88%. We identify key factors influencing prediction accuracy, including data preprocessing, feature selection, and kernel functions.