Stock predictions with RNN
Python
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README.md

rnn_stock_predictions

data Crawling, Pretreatment, Processing, Training, Model Visualization -> AUTOMATION

requirments

  • Python 3.5.3
  • tensorflow 1.1.0
  • Pandas_datareader
  • numpy
  • matplotlib
  • datetime

Run

  • python apple.py
  • python kospi.py
  • tensorboard --logdir=./tensorflowlog
  • tensorboard http://localhost:6006/
    graphs

Model

  • RNN + Fully connected layer
  • Train : Test = 70 : 30
  • Train Period = 2010.1.2~2017.5.27
  • Predictions Period = 2017.5.28~2017.6.7
  • Real Period = 2017.6.8

Results

  • Alphabet 0.050(RMSE) 1004.28(Real) 1001.59(Predictions)
  • apple 0.020(RMSE) 154.99(Real) 155.37 (Predictions)
  • berkshire 0.016(RMSE) 250305(Real) 249621 (Predictions)
  • hyundai_motor 0.020(RMSE) 160000(Real) 159000 (Predictions)
  • kospi 0.022(RMSE) 2363.57(Real) 2360.14(Predictions)
  • samsung_electronics 0.022(RMSE) 2258000(Real) 2265000(Predictions)
  • sk_hynix 0.024(RMSE) 56700(Real) 56500(Predictions)
  • berkshire

berkshire_err berkshire_value rnn_tensorboard

Reference