Stock Performance Evaluation for Portfolio Design from Different Sectors
of the Indian Stock Market
- URL: http://arxiv.org/abs/2208.07166v1
- Date: Fri, 1 Jul 2022 10:31:03 GMT
- Title: Stock Performance Evaluation for Portfolio Design from Different Sectors
of the Indian Stock Market
- Authors: Jaydip Sen, Arpit Awad, Aaditya Raj, Gourav Ray, Pusparna Chakraborty,
Sanket Das, Subhasmita Mishra
- Abstract summary: We have tried to predict the future value of a few stocks from six important sectors of the Indian economy.
As part of building an efficient portfolio, we have studied multiple portfolio optimization theories.
We have built a minimum variance portfolio and optimal risk portfolio for all the six chosen sectors.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The stock market offers a platform where people buy and sell shares of
publicly listed companies. Generally, stock prices are quite volatile; hence
predicting them is a daunting task. There is still much research going to
develop more accuracy in stock price prediction. Portfolio construction refers
to the allocation of different sector stocks optimally to achieve a maximum
return by taking a minimum risk. A good portfolio can help investors earn
maximum profit by taking a minimum risk. Beginning with Dow Jones Theory a lot
of advancement has happened in the area of building efficient portfolios. In
this project, we have tried to predict the future value of a few stocks from
six important sectors of the Indian economy and also built a portfolio. As part
of the project, our team has conducted a study of the performance of various
Time series, machine learning, and deep learning models in stock price
prediction on selected stocks from the chosen six important sectors of the
economy. As part of building an efficient portfolio, we have studied multiple
portfolio optimization theories beginning with the Modern Portfolio theory. We
have built a minimum variance portfolio and optimal risk portfolio for all the
six chosen sectors by using the daily stock prices over the past five years as
training data and have also conducted back testing to check the performance of
the portfolio. We look forward to continuing our study in the area of stock
price prediction and asset allocation and consider this project as the first
stepping stone.
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