Stock Market Analysis With Machine Learning

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About the Project

The purpose of this project is to investigate the profitability of various algorithmic trading strategies. As part of this investigation, we predict stock prices on both weekly and monthly intervals using multiple machine learning methods. These methods perform inference over technical and fundamental market indicators.

Many researchers have worked on the problem of applying machine learning algorithms to market data. Often, they evaluate their methods with the accuracy of their models’ predictions. However, if the purpose of the model is to facilitate an intelligent trading strategy, then the performance of the strategy should be used in conjunction with accuracy to evaluate the model. Therefore, we use both accuracy and back- testing to evaluate our models.


  • Kyle Thompson, Computer Science
  • Lubomir Stanchev, Computer Science