Authors: Dr. S. Sheeja, Bavani. G, Dhanish Ahamad. M
Abstract: In a modern financial world, investors are faced with various challenges such as market volatility, a large volume of financial information, and a lack of personalized investment advice. In this context, existing investment systems involve processing financial information and employing decision-making techniques. These techniques are no longer sufficient in today's changing market environment.In this paper, a new concept is introduced to develop an "AI Supported Investment Portfolio Management System." This system will help users make intelligent investment decisions using machine learning and financial analytics. In this project, financial information is used to analyze the stock market using various financial parameters such as "Compound Annual Growth Rate," "Volatility," and "Maximum Drawdown." Machine learning algorithms such as K-Means clustering are used to classify assets based on various risk levels. In this project, regression algorithms are used to predict stock price trends. In addition, a recommendation system is also incorporated in this project to make intelligent investment decisions. In this project, a SIP planner is used to analyze long-term investments. In this project, an interactive interface is developed using Streamlit to better understand financial information.The above system demonstrates the effective application of Artificial Intelligence in the field of finance and creates a data-driven and user-centric approach towards the development of the financial strategy
