Simulation Based Exploration of Stock Market Using LSTM Model

Authors

  • Tetarwal R Computer Science Department, Sharda University, Greater Noida, India https://orcid.org/0009-0005-3576-0629
  • Tushir R Computer Science Department, Sharda University, Greater Noida, India

DOI:

https://doi.org/10.26438/ijcse/v11i4.2629

Keywords:

Stock Market, Predicting, LSTM Model,, RNN Model, Prices, Complex Data, Density

Abstract

In today’s world the stock market has a huge impact on the economy making it difficult for stock market investors to predict stock prices. Financial market investors cannot use simple models to more accurately predict stock prices to invest in stocks. Deep learning helps computer to solve complex problems which humans takes more time to solve. This paper is based on developing a model to predict inventory value using recurrent neural network (RNN) and long- short term memory model (LSTM).

References

[1] A S Pradeep, Soren Goyal and M. Miller, “Detection of statistical arbitrage using machine learning techniques in Indian Stock market”, PhD Thesis, Computer Science Department, IIT Kanpur, 2019.

[2] Dhiraj Mundada, Gaurav Chhaparwal, Sachin Chaudhari, Trupti Bhamare, “Stock Value Prediction System”, International Journal on Recent and Innovation Trends in Computing and Communication, Vol. 3, Issue 4, pp. 2217 - 2219, 2015. https://doi.org/10.17762/ijritcc.v3i4.4214

[3] Rakhi Mahant, Trilok Nath Pandey, Alok Kumar Jagadev and, Satchidananda Dehuri, “Optimized Radial Basis Functional Neural Network for Stock Index Prediction”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Vol. 7, Issue 11, pp. 1252 - 1257, 2016. Doi: 10.1109/ICEEOT.2016.7754884

[4] S. Hochreiter and J. Schmid Huber, “Long Short- Term Memory”, Neural Computation, Vol.9, Issue 8, pp. 1735 - 1780, 1997. https://doi.org/10.1162/neco.1997.9.8.1735

[5] S. Sarode, H. G. Tolani, P. Kak and C. S. Lifna, "Stock Price Prediction Using Machine Learning Techniques”, International Conference on Intelligent Sustainable Systems (ICISS), Vol 5, Issue 3, pp. 177 - 181, 2019. Doi: 10.1109/ISS1.2019.8907958.

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Published

2023-04-30
CITATION
DOI: 10.26438/ijcse/v11i4.2629
Published: 2023-04-30

How to Cite

[1]
R. Tetarwal and R. Tushir, “Simulation Based Exploration of Stock Market Using LSTM Model”, Int. J. Comp. Sci. Eng., vol. 11, no. 4, pp. 26–29, Apr. 2023.

Issue

Vol. 11 No. 4 (2023): IJCSE April Edition

Section

Research Article

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