International Journal of Innovative Research in Engineering and Management
Year: 2021, Volume: 8, Issue: 6
First page : ( 53) Last page : ( 59)
Online ISSN : 2350-0557.
DOI: 10.55524/ijirem.2021.8.6.10 |
DOI URL: https://doi.org/10.55524/ijirem.2021.8.6.10
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Tanushka M , Shilpa S Devadiga, Nagamani G
During the past few months, a lot of people, mostly millennials, have begun to invest money as they have realized its importance and power. An investment in the right combination of stock can go a long way. In the current scenario, the new investors are playing it smart by choosing safe options like mutual funds. But in reality, a diversified portfolio, though a little riskier than the former, guarantees better returns. Our project is based on helping these investors make wise decisions as per their requirements and make sure they receive the maximum returns given their preferred level of risk. We plan on making this process of making a portfolio easy for these investors. The market that is being considered is National Stock Exchange (NSE). The stocks that will be examined will be those enlisted in the NSE. We will be predicting the stock growth using appropriate methods and using this data for further steps. The stock growth prediction has been done using multiple approaches. Seeking the user’s point of view is extremely important if we want to build a customized portfolio, hence he/she will have to take a small quiz to throw some light on his/her expectations from the portfolio. The portfolio will be built based on the user preferences. Following this, risk minimization will be done using various methods. The agenda is to produce a portfolio that gives maximum returns for the specified risk level. The project has been programmed in Python using a number of libraries and extensions. This project is still in the research and testing stages. It is highly recommended not to take the following findings as investment advice.
Department of Computer Science and Engineering, PES University, Bangalore, Karnataka, India
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