Stock Price Prediction is one of the most difficult task to do, in financial sector. There are many factors involved in the prediction like physical factors vs. psychological, rational and irrational behaviour, etc. All these aspects combine to make share prices volatile and very difficult to predict with a high degree of accuracy. But we can predict a similar trend using previous data trends of a company's stock and to do so we will use a LSTM model to mimic the strategy used by quants.
We are using Google's stock dataset.
The motivation of this project was to implement the model using LSTM and to compare its performance with existing models.
- Numpy
conda install numpy - Pandas
conda install pandas - Matplotlib
conda install matplotlib - Keras
conda install keras - Spyder IDE
conda install spyder
- single attribute prediction
- predicted open price
- predicted close price
- hyperparameter optimization
- feature importance
- multiple attribute prediction
- predicted open price
- predicted close price
- trading application
- future stock predictionults