Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Model

TL;DR

This paper develops an optimized LSTM model for stock price prediction and constructs sector-wise portfolios in India to maximize returns and manage risk, demonstrating high prediction accuracy.

Contribution

It introduces a systematic approach combining LSTM-based prediction with optimized portfolio construction for Indian economic sectors.

Findings

LSTM model achieves high accuracy in stock price prediction.

Optimized portfolios outperform baseline strategies.

Sector-wise portfolios show significant risk-return improvements.

Abstract

Accurate prediction of future prices of stocks is a difficult task to perform. Even more challenging is to design an optimized portfolio with weights allocated to the stocks in a way that optimizes its return and the risk. This paper presents a systematic approach towards building two types of portfolios, optimum risk, and eigen, for four critical economic sectors of India. The prices of the stocks are extracted from the web from Jan 1, 2016, to Dec 31, 2020. Sector-wise portfolios are built based on their ten most significant stocks. An LSTM model is also designed for predicting future stock prices. Six months after the construction of the portfolios, i.e., on Jul 1, 2021, the actual returns and the LSTM-predicted returns for the portfolios are computed. A comparison of the predicted and the actual returns indicate a high accuracy level of the LSTM model.