mlsanityData to 7 Oct 2026

Stock Portfolio Optimization Using a Deep Learning LSTM Model

arXiv 2111.04709 ↗First posted 8 Nov 2021q-fin.PM cs.LGcited by 9

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Abstract (arXiv)

Predicting future stock prices and their movement patterns is a complex problem. Hence, building a portfolio of capital assets using the predicted prices to achieve the optimization between its return and risk is an even more difficult task. This work has carried out an analysis of the time series of the historical prices of the top five stocks from the nine different sectors of the Indian stock market from January 1, 2016, to December 31, 2020. Optimum portfolios are built for each of these sectors. For predicting future stock prices, a long-and-short-term memory (LSTM) model is also designed and fine-tuned. After five months of the portfolio construction, the actual and the predicted returns and risks of each portfolio are computed. The predicted and the actual returns of each portfolio are found to be high, indicating the high precision of the LSTM model.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 7 of its 21 references that are in the map. First posted on arXiv 8 Nov 2021.

Builds on

7 of 21 references.

References · 7

  1. 2017Autoregressive Convolutional Neural Networks for Asynchronous Time Seriescited by 31
  2. 2020Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Modelscited by 24
  3. 2019A Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processingcited by 23
  4. 2021Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Modelscited by 15
  5. 2021Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCHcited by 12
  6. 2021Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Modelcited by 11
  7. 2018A Relaxed Optimization Approach for Cardinality-Constrained Portfolio Optimizationcited by 1

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 3; 2023: 3; 2024: 2.

9 papers.

  1. 2022Hierarchical Risk Parity and Minimum Variance Portfolio Design on NIFTY 50 Stockscited by 4
  2. 2022Designing Efficient Pair-Trading Strategies Using Cointegration for the Indian Stock Marketcited by 4
  3. 2021Analysis of Sectoral Profitability of the Indian Stock Market Using an LSTM Regression Modelcited by 3
  4. 2022A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stockscited by 3
  5. 2024Neuroevolution Neural Architecture Search for Evolving RNNs in Stock Return Prediction and Portfolio Tradingcited by 1
  6. 2023A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Marketcited by 0
  7. 2023Portfolio Optimization: A Comparative Studycited by 0
  8. 2023Performance Evaluation of Equal-Weight Portfolio and Optimum Risk Portfolio on Indian Stockscited by 0
  9. 2024Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learningcited by 0