Predicting the Direction of Stock Market Prices using a Random Forest Classifier

In this demo I will show how to predict if the closing price of Apple, General Electric and Samsung Electronics is moving up or down. We do this with the help of a Random Forest Classifier.

I tried to replicate the result from a research paper authored by Luckyson Khaidem, Snehanshu Saha, Sudeepa Roy Dey which is describing the following concept:

• Data Preprocessing
  • exponentially smoothing
• Features
  • Relative Strength Index
  • Stochastic Oscillator
  • Williams %R
  • Moving Average Convergence Divergence
  • Price Rate of Change
  • On Balance Volume
• Labels
  • Sign(closei+d − closei)
• Ticker Symbols
  • Apple (NASDAQ:AAPL)
  • General Electric (NASDAQ:GE)
  • Samsung Electronics Co. Ltd (SSNLF)

The solution has been implemented in Scala using Jupyter with the BeakerX kernel using the following libraries

• Investor
• Spark & MLLib

The document can be found in the following Gist.