Leveraging Machine Learning Techniques to Study The Stock Market Dynamics in India

Abstract

Prokarsha Kumar Ghosh

This abstract explores the application of time series analysis, machine learning, and deep learning methods in forecasting long-term stock market trends in the Indian financial market. Even though short-term forecasting is challenging due to the complexities of the markets and the emotional factors it has involved, long-term trends become more predictable in data science techniques. Recent studies have been able to showcase that time series analysis happens to be an effective technique in recognizing patterns and predicting future movements based on historical data. One may also observe the inter-stock relationships and understand how those relate to market trends or potential investments. Ongoing advancements in statistical and analytical methods are driving significant progress in stock market analysis. As machine learning techniques keep improving, they will help make forecasting models better, giving investors and financial experts more useful information to make smarter decisions. These developments are poised to improve stock market prediction and offer crucial insights into market behaviour, benefiting stakeholders in the financial sector.

PDF