danish-mehmood / randomforest-stockpredictor

Utilizing the ensemble method of random forests to predict stock prices.

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.