Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model

• URL: http://arxiv.org/abs/2203.01326v1
• Date: Wed, 2 Mar 2022 14:37:30 GMT
• Title: Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Model
• Authors: Jaydip Sen, Sidra Mehtab, Abhishek Dutta, Saikat Mondal
• Abstract summary: 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. An LSTM regression model is also designed for predicting future stock prices.
• Score: 1.1879716317856945
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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