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

TL;DR

This paper develops an LSTM-based model to predict stock prices and uses these predictions to design optimized portfolios across seven Indian economic sectors, achieving high accuracy in return and risk estimation.

Contribution

It introduces a novel approach combining LSTM prediction with portfolio optimization for Indian stocks, demonstrating high prediction accuracy and effective portfolio design.

Findings

LSTM model accurately predicts stock prices.

Optimized portfolios show high return and risk estimation accuracy.

Method applied to seven Indian economic sectors.

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.