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Stock Predictor and Portfolio Optimizer

A novice's attempt for (weekly) stock prices prediction and portfolio optimization.

###Technologies used -

  • Python 3
  • Scipy
  • Scikit-learn
  • matplotlib

###Data Source

###Major Features

  • Prediction of stock prices on weekly basis (predicting next week's prices for a given stock)
  • Optimizing portfolio distributions ( optimum ratio of each stock in a portfolio to potentialy maximize profits )

###Algorithms and implementation mechanisms

  • Weekly prediction is being done using KNN Regressor using "Bollinger Band Value" and "Simple Moving Average" as input features.
  • Stock porfolio optimizer is done for maximizing the "Sharpe Ratio" or "culumative returns", using scipy minimizer (minimizing for -1 * value)

###Testing and results

  • This application has been tested for National Stock Exchange, India. The weekly predictions have upto 75 % corelation with the actual results, for the leading (largest market capitalization) stocks.

###TODO

  • Add all dependancies in requirements.txt
  • Creating web services
  • Creating Web-based front-end.
  • Improving accuracy by adding more Fundamental and Technical features

###Notes

  • As I've mentioned, this implementation is at early stage. If you are an Machine Learning or Stock Market Enthusiast / Expert, feel free to suggest improvements / corrections by creating an issue (or you contact me at [email protected] )
  • As I have beginner-level skillset in Python programming language, I might have missed many of the best practices and architectural patterns specific to Python ecosystem, please feel free to suggest some improvements.
  • This application was part of my academic project coursework (Major Project, Engineering Final Year, Information Technology)

###Credits