Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning Models

Author:

Mehtab Sidra,Sen Jaydip,Dutta Abhishek

Publisher

Springer Singapore

Reference26 articles.

1. Sen, J., Datta Chaudhuri, T.: 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. J. Econ. Libr. 3(2), 303–326 (2016)

2. Sen, J., Datta Chaudhuri, T.: An investigation of the structural characteristics of the indian IT sector and the capital goods sector - an application of the R programming language in time series decomposition and forecasting. J. Insur. Financ. Manag. 1(4), 68–132 (2016)

3. Sen, J., Datta Chaudhuri, T.: Understanding the sectors of indian economy for portfolio choice. Int. J. Bus. Forecast. Mark. Intell. 4(2), 178–222 (2018)

4. Sen, J., Datta Chaudhuri, T.: A robust predictive model for stock price forecasting. In: Proceedings of the 5th International Conference on Business Analytics and Intelligence, Bangalore, India, 11–13 December 2017 (2017)

5. Sen, J.: Stock price prediction using machine learning and deep learning frameworks. In: Proceedings of the 6th International Conference on Business Analytics and Intelligence, Bangalore, India, 20–22 December 2018 (2018)

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