mlsanityData to 7 Oct 2026

Analysis of Sectoral Profitability of the Indian Stock Market Using an LSTM Regression Model

arXiv 2111.04976 ↗First posted 9 Nov 2021cs.LG q-fin.CPcited by 3

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Abstract (arXiv)

Predictive model design for accurately predicting future stock prices has always been considered an interesting and challenging research problem. The task becomes complex due to the volatile and stochastic nature of the stock prices in the real world which is affected by numerous controllable and uncontrollable variables. This paper presents an optimized predictive model built on long-and-short-term memory (LSTM) architecture for automatically extracting past stock prices from the web over a specified time interval and predicting their future prices for a specified forecast horizon, and forecasts the future stock prices. The model is deployed for making buy and sell transactions based on its predicted results for 70 important stocks from seven different sectors listed in the National Stock Exchange (NSE) of India. The profitability of each sector is derived based on the total profit yielded by the stocks in that sector over a period from Jan 1, 2010 to Aug 26, 2021. The sectors are compared based on their profitability values. The prediction accuracy of the model is also evaluated for each sector. The results indicate that the model is highly accurate in predicting future stock prices.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 12 of its 60 references that are in the map. First posted on arXiv 9 Nov 2021.

Builds on

12 of 60 references.

References · 12

  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

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Cited by year

Citing papers per year: 2023: 2; 2024: 1.

3 papers.

  1. 2023A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Marketcited by 0
  2. 2023Performance Evaluation of Equal-Weight Portfolio and Optimum Risk Portfolio on Indian Stockscited by 0
  3. 2024Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learningcited by 0