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Stock Price Prediction using Machine Learning Techniques
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README.md

Stock Market Price Predictor using Supervised Learning

Aim

To examine a number of different forecasting techniques to predict future stock returns based on past returns and numerical news indicators to construct a portfolio of multiple stocks in order to diversify the risk. We do this by applying supervised learning methods for stock price forecasting by interpreting the seemingly chaotic market data.

Setup Instructions

    $ workon myvirtualenv                                  [Optional]
    $ pip install -r requirements.txt
    $ python scripts/Algorithms/regression_models.py <input-dir> <output-dir>

Download the Dataset needed for running the code from here.

Project Concept Video

Project Concept Video

Methodology

  1. Preprocessing and Cleaning
  2. Feature Extraction
  3. Twitter Sentiment Analysis and Score
  4. Data Normalization
  5. Analysis of various supervised learning methods
  6. Conclusions

Research Paper

Datasets used

  1. http://www.nasdaq.com/
  2. https://in.finance.yahoo.com
  3. https://www.google.com/finance

Useful Links

References

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