MATHEMATICAL MODEL FOR STOCK PRICE PREDICTION USING LSTM NETWORKS IN PYTHON JUPYTER NOTEBOOK
1. VIVEK PARKASH, Assistant Professor, Dyal Singh College, India
Long short-term memory abbreviated as LSTM
is an artificial neural network used in the fields of artificial
intelligence and deep learning. I am going to LSTM (long short term
memory) networks and python coding in jupyter notebook for price movement predictions
for TCS stock listed on NSE. In the end it will be concluded that the predicted
movement of TCS stock price is similar to the actual one. Moreover next 20 days
opening prices will be calculated based on previous few days price data.
So, our model has successfully predicted
stock TCS move for the next 20 days. This graph shows that how well the share has
moved during the prediction period. This above described model is for TCS stock.
This model can be applied to any other stock. All we have to do is to import the
corresponding stock data from yahoo finance. We can change other parameters accordingly
and tweak the parameters to get better results.
Sole author Dr. Vivek Parkash has done work in this research paper himself and fully own the responsibility.
Got funding from nowhere for this paper.
No Conflict of Interest
data will be shared as required
used LSTM Python with different libraries and functions
I thank my family for the cooperation.
Dyal Singh College, Assistant Professor, India
Copyright: ©2024 Corresponding Author. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PARKASH, VIVEK. “MATHEMATICAL MODEL FOR STOCK PRICE PREDICTION USING LSTM NETWORKS IN PYTHON JUPYTER NOTEBOOK.” Scientific Research Journal of Science, Engineering and Technology, vol. 1, no. 2, 2023, pp. 1-10, https://isrdo.org/journal/SRJSET/currentissue/mathematical-model-for-stock-price-prediction-using-lstm-networks-in-python-jupyter-notebook
PARKASH, V. (2023). MATHEMATICAL MODEL FOR STOCK PRICE PREDICTION USING LSTM NETWORKS IN PYTHON JUPYTER NOTEBOOK. Scientific Research Journal of Science, Engineering and Technology, 1(2), 1-10. https://isrdo.org/journal/SRJSET/currentissue/mathematical-model-for-stock-price-prediction-using-lstm-networks-in-python-jupyter-notebook
PARKASH VIVEK, MATHEMATICAL MODEL FOR STOCK PRICE PREDICTION USING LSTM NETWORKS IN PYTHON JUPYTER NOTEBOOK, Scientific Research Journal of Science, Engineering and Technology 1, no. 2(2023): 1-10, https://isrdo.org/journal/SRJSET/currentissue/mathematical-model-for-stock-price-prediction-using-lstm-networks-in-python-jupyter-notebook
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