• Arbaz Attar
• Shubham Narale
• Pranay Mule
• Piyush Kulkarni
• Prof. Ms. Jaitee Bankar

Portfolio management is the concept of determining the proportions of various assets to be held in a portfolio in order to maximize return while minimizing risk exposure. Portfolio optimization is a critical component in financial management and investment banking. Constructing an optimal portfolio by selecting the best possible combinations of different portfolios is a computationally difficult problem with exponential complexity. It is widely assumed that public sentiment is related to financial markets. Different types of machine learning models have recently been used with positive results for short-term financial market prediction. However, historical returns do not appear to follow the normal distribution hypothesis. However, when using long short-term memory networks in addition to historical data, sentiment analysis yields better results. In this project, we want to use AI/ML to predict portfolio risk and provide insights into how stocks will perform. We will train our model using datasets obtained from the Yahoo Financial API that include historical data from the top 100 companies (NIFTY 100) in the NSE and BSE from 2010 to 2021.

Portfolio Management, Machine Learning Models (AI/ML), Historical Data, Financial Markets, Data Vector, ML algorithm, Efficiency, etc.

"INVESTMENT PORTFOLIO MANAGEMENT SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.o57-o61, May-2023, Available :http://www.jetir.org/papers/JETIR2305F07.pdf

"INVESTMENT PORTFOLIO MANAGEMENT SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppo57-o61, May-2023, Available at : http://www.jetir.org/papers/JETIR2305F07.pdf