Enhancing Investment Decision-Making: A Comprehensive Approach through Fundamental, Technical and Sentiment Analysis with Machine Learning and Deep Learning Algorithms

In this dynamically changing realm of the Indian financial markets, effective investment strategies drives the need to innovative new methodologies integrating diverse analyses and leveraging advanced technologies. This paper proposes a comprehensive study revolving around the Indian market dynamics, which aims to enhance the investment decision-making via the integration of fundamental, technical, and sentiment analyses using state-of-art machine learning and deep learning algorithms. The core of this methodology implements an Integrated Analysis Framework that amalgamates fundamental ratios, historical and volumetric market trends, various technical indicators, and sentiment variables, leveraging machine learning algorithms to extract meaningful insights from extensive datasets by predictive modeling and sentiment analysis. The framework integrates the fundamental analysis for six different stocks of the Indian market from 2018 to 2023 along with the utilization of Twitter data for sentiment analysis, in combination with pre-trained models, and the calculation of over 80 technical indicators for technical analysis. Results from diverse analyses are synthesized to enhance predictive accuracy of calculating the closing prices and trends using different regression models and time-series analysis. Tailored to the scenario of the Indian market, this methodology aims to provide actionable insights and recommendations for investors.