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Research Article
Stock Price Prediction Using LSTM
Sampada A. Kulkarni1
Shubham Gurav2
Aditya Lahade3
Deepak Gudavalekar4
Nagnath Sangale5
1Asst.Prof. Dept. of I.T., P.E.S Modern College of Engineering, Savitribai Phule Pune University, Maharashtra, India. 2345Dept. of I.T., P.E.S Modern College of Engineering, Savitribai Phule Pune University, Maharashtra, India.
Published Online: January-April 2024
Pages: 22-24
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20240301001
References
1. J. Sen and T. Datta Chaudhuri, "An alternative framework for time series decomposition and forecasting and its relevance for portfolio
choice - a comparative study of the Indian consumer durable and small-cap sector," Journal of Economics Library, vol. 3, no. 2, pp. 303 -
326, 2016.
2. J. Sen and T. Datta Chaudhuri, "Understanding the sectors of Indian economy for portfolio choice," International Journal of Business
Forecasting and Marketing Intelligence, vol. 4, no. 2, pp. 178-222, 2018
3. S. Hochreiter and J. Schmidhuber, “Long short-term memory,” MIT Press, vol. 9, no. 8, pp. 1735–1780, 1997.
4. S. Mehtab and J. Sen, “A time series analysis-based stock price prediction using machine learning and deep learning models”, Technical
Report, No: NSHM_KOL_2020_SCA_DS_1, NSHM Knowledge Campus, Kolkata, INDIA. DOI: 10.13140/RG.2.2.14022.22085/2.
5. Y. Hu, “Stock market timing model based on convolutional neural network– a case study of Shanghai composite index,” Finance&
Economy, vol. 4, pp. 71–74, 2018.
choice - a comparative study of the Indian consumer durable and small-cap sector," Journal of Economics Library, vol. 3, no. 2, pp. 303 -
326, 2016.
2. J. Sen and T. Datta Chaudhuri, "Understanding the sectors of Indian economy for portfolio choice," International Journal of Business
Forecasting and Marketing Intelligence, vol. 4, no. 2, pp. 178-222, 2018
3. S. Hochreiter and J. Schmidhuber, “Long short-term memory,” MIT Press, vol. 9, no. 8, pp. 1735–1780, 1997.
4. S. Mehtab and J. Sen, “A time series analysis-based stock price prediction using machine learning and deep learning models”, Technical
Report, No: NSHM_KOL_2020_SCA_DS_1, NSHM Knowledge Campus, Kolkata, INDIA. DOI: 10.13140/RG.2.2.14022.22085/2.
5. Y. Hu, “Stock market timing model based on convolutional neural network– a case study of Shanghai composite index,” Finance&
Economy, vol. 4, pp. 71–74, 2018.
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