Portfolio Optimization on NIFTY Thematic Sector Stocks Using an LSTM Model
Abstract
Portfolio optimization has been a broad and intense area of interest for quantitative and statistical finance researchers and financial analysts. It is a challenging task to design a portfolio of stocks to arrive at the optimized values of the return and risk. This paper presents an algorithmic approach for designing optimum risk and eigen portfolios for five thematic sectors of the NSE of India. The prices of the stocks are extracted from the web from Jan 1, 2016, to Dec 31, 2020. Optimum risk and eigen portfolios for each sector are designed based on ten critical stocks from the sector. An LSTM model is designed for predicting future stock prices. Seven months after the portfolios were formed, on Aug 3, 2021, the actual returns of the portfolios are compared with the LSTM-predicted returns. The predicted and the actual returns indicate a very high-level accuracy of the LSTM model.
Keywords
Cite
@article{arxiv.2202.02723,
title = {Portfolio Optimization on NIFTY Thematic Sector Stocks Using an LSTM Model},
author = {Jaydip Sen and Saikat Mondal and Sidra Mehtab},
journal= {arXiv preprint arXiv:2202.02723},
year = {2022}
}
Comments
The is the preprint version of our published paper listed in the IEEE Xplore. The final paper is published in the Proceedings of the IEEE International Conference on Data Analytics for Business and Industry, pp. 364-369, Bahrain, October 25-26, 2021. The preprint consists of 6 pages and it contains 10 figures and 16 tables