Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Model
This work addresses portfolio optimization and stock prediction for investors in specific Indian economic sectors, but it is incremental as it applies an existing LSTM method to new data.
This paper tackled stock price prediction and portfolio design for Indian sectors using an LSTM model, achieving high accuracy in predicting returns compared to actual data from July 2021.
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.