Prediction of Stock Prices Using LSTM network

Stock and ETFs prices are predicted using LSTM network (Keras-Tensorflow).

Github code: https://github.com/omerbsezer/stockPricesPredictionWithLSTM

  • Stock prices are downloaded from finance.yahoo.com.
  • Closed value (column[5]) is used in the network.
  • Values are normalized in range (0,1).
  • Datasets are splitted into train and test sets, 50% test data, 50% training data.
  • Keras-Tensorflow is used for implementation.
  • LSTM network consists of 25 hidden neurons, and 1 output layer (1 dense layer).
  • LSTM network features input: 1 layer, output: 1 layer , hidden: 25 neurons, optimizer:adam, dropout:0.1, timestep:240, batchsize:240, epochs:1000 (features can be further optimized).
  • Root mean squared errors are calculated.
  • Output files: lstm_results (consists of prediction and actual values), plot file (actual and prediction values).


Reference: https://www.kaggle.com/pablocastilla/predict-stock-prices-with-lstm/notebook

What is LSTM? (General Information) https://en.wikipedia.org/wiki/Long_short-term_memory

Keras: https://keras.io/

Tensorflow: https://www.tensorflow.org/


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