Exploring Machine Learning Approaches for Analysis and Prediction in the Indian Stock Market

Predicting the Indian stock market with accuracy is a considerable challenge, mainly due to its nonlinear time series nature. Nevertheless, the advent of diverse Machine Learning methodologies has sparked an extensive investigation in this domain. Primarily, scholarly inquiries have concentrated on harnessing Supervised Machine Learning algorithms for predicting the prices of individual stocks and forecasting movements in stock indices. Furthermore, researchers have explored the utilization of Unsupervised Machine Learning algorithms and statistical approaches to anticipate stock prices. Another area of exploration involves constructing portfolios that maximize profits while minimizing risks. Moreover, the influence of social media, which generates an abundance of data, has become a crucial factor impacting experts' decisions to buy or sell stocks. This survey aims to identify the various approaches researchers employ to improve the accuracy of machine learning algorithms in analyzing the Indian Stock Market. It highlights the importance of taking into account all pertinent aspects of the stock market prior to making predictions