mlsanityData to 14 Oct 2026

Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learning

arXiv 2407.01572 ↗First posted 28 May 2024q-fin.CP cs.LG q-fin.PMcited by 0

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Abstract (arXiv)

This paper explores using a deep learning Long Short-Term Memory (LSTM) model for accurate stock price prediction and its implications for portfolio design. Despite the efficient market hypothesis suggesting that predicting stock prices is impossible, recent research has shown the potential of advanced algorithms and predictive models. The study builds upon existing literature on stock price prediction methods, emphasizing the shift toward machine learning and deep learning approaches. Using historical stock prices of 180 stocks across 18 sectors listed on the NSE, India, the LSTM model predicts future prices. These predictions guide buy/sell decisions for each stock and analyze sector profitability. The study's main contributions are threefold: introducing an optimized LSTM model for robust portfolio design, utilizing LSTM predictions for buy/sell transactions, and insights into sector profitability and volatility. Results demonstrate the efficacy of the LSTM model in accurately predicting stock prices and informing investment decisions. By comparing sector profitability and prediction accuracy, the work provides valuable insights into the dynamics of the current financial markets in India.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 70 references that are in the map. First posted on arXiv 28 May 2024.

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19 of 70 references.

References · 19

  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. 2020Stock Price Prediction Using CNN and LSTM-Based Deep Learning Modelscited by 21
  5. 2020A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Modelscited by 18
  6. 2021Accurate Stock Price Forecasting Using Robust and Optimized Deep Learning Modelscited by 15
  7. 2020Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Timeseriescited by 13
  8. 2021Volatility Modeling of Stocks from Selected Sectors of the Indian Economy Using GARCHcited by 12
  9. 2020Robust Analysis of Stock Price Time Series Using CNN and LSTM-Based Deep Learning Modelscited by 11
  10. 2021Profitability Analysis in Stock Investment Using an LSTM-Based Deep Learning Modelcited by 11
  11. 2021Stock Portfolio Optimization Using a Deep Learning LSTM Modelcited by 9
  12. 2021Design and Analysis of Robust Deep Learning Models for Stock Price Predictioncited by 6
7 more
  1. 2022Robust Portfolio Design and Stock Price Prediction Using an Optimized LSTM Modelcited by 6
  2. 2021Stock Price Prediction Using Time Series, Econometric, Machine Learning, and Deep Learning Modelscited by 5
  3. 2022Portfolio Optimization on NIFTY Thematic Sector Stocks Using an LSTM Modelcited by 5
  4. 2022Hierarchical Risk Parity and Minimum Variance Portfolio Design on NIFTY 50 Stockscited by 4
  5. 2022Precise Stock Price Prediction for Optimized Portfolio Design Using an LSTM Modelcited by 4
  6. 2022Designing Efficient Pair-Trading Strategies Using Cointegration for the Indian Stock Marketcited by 4
  7. 2021Analysis of Sectoral Profitability of the Indian Stock Market Using an LSTM Regression Modelcited by 3

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