Comparative Analysis of Machine Learning Algorithms to Forecast Indian Stock Market

Abstract

Forecasting the stock market is a complex and challenging task, as it involves analyzing a vast amount of data and taking into account various economic, political, and social factors. This paper presents an overview of different approaches and techniques used for stock market forecasting, including fundamental analysis and machine learning. The study also highlights the different algorithms used and discusses their effectiveness in predicting the stock market. This research proposes to use five different algorithms as Decision Trees, Random forest, Generalized Linear model,Gradient boosted trees, and Support Vector Machines. This research identifies models that are close to real predictions. These algorithms are applied to BSE index data from November 2017 to February28, 2023.