Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model
Abstract
Accurate prediction of future prices of stocks is a difficult task to perform. Even more challenging is to design an optimized portfolio of stocks with the identification of proper weights of allocation to achieve the optimized values of return and risk. We present optimized portfolios based on the seven sectors of the Indian economy. The past prices of the stocks are extracted from the web from January 1, 2016, to December 31, 2020. Optimum portfolios are designed on the selected seven sectors. An LSTM regression model is also designed for predicting future stock prices. Five months after the construction of the portfolios, i.e., on June 1, 2021, the actual and predicted returns and risks of each portfolio are computed. The predicted and the actual returns indicate the very high accuracy of the LSTM model.
Keywords
Cite
@article{arxiv.2203.01326,
title = {Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model},
author = {Jaydip Sen and Sidra Mehtab and Abhishek Dutta and Saikat Mondal},
journal= {arXiv preprint arXiv:2203.01326},
year = {2022}
}
Comments
This is the accepted version of our paper in the IEEE 19th OITS International Conference on Information Technology (OCIT 21). The final version is available in the IEEE Xplore. The paper consists of 6 pages and it includes 9 figures and 20 tables. arXiv admin note: substantial text overlap with arXiv:2202.02723, arXiv:2111.04709