Stock Market Prevision Using Data Mining

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This project comprehends the development of a knowledge discovering process for historical financial data about the IBM company.
The algorithm is able to predict (based on stock value, sales volume, profit, etc) how stocks are most likely to evolve in a quarter-year, half-year and annual basis. 
Three steps where taken:

  • original data conversion to a format suitable for the data mining algorithm;
  • application of pattern recognition algorithms, which will make the prevision itself:
  • stock trading simulation, so the real performance of the developed system can be quantified.


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