Random Forest Stock Predictor

Utilizing the ensemble method of random forests to predict stock prices, based on the results of Khaidem, Saha, & Dey (2016). Group course project for Ensemble Methods of Machine Learning, summer semester 2017 at the University of Osnabrück.

Usage

1. Clone repo with:
   git clone https://github.com/johnberroa/RandomForest-StockPredictor.git
2. Use the Technical Analysis Notebook.ipynb to generate indicators by running the whole notebook. This will save them to the file data_preprocces.csv.
3. Next run the Random Forest Notebook.ipynb. The Results can be found in the results directory.