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Automated Investment Analysis

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With the recent financial crisis in America, investors have received much of the blame and have been tasked with improving investment techniques to prevent another recession of similar magnitude. Here we look to develop new methods for investing using algorithms that automate the process of deciding whether to buy, sell, or avoid a stock. These algorithms use both technical and fundamental data to improve investing success by removing the factor of human emotion from trading, reducing risk of loss due to greed. We ultimately find that with a careful application of technical and fundamental data, as well as a thorough understanding patterns in financial markets, it is possible to develop an automated trading strategy that can profitably trade stocks and currencies.

  • This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
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  • E-project-053011-152817
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  • 2011
Date created
  • 2011-05-30
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