Student Work

Neural Net-Based Software for Trading Initial Public Offerings

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With the number of Initial Public Offerings (IPOs) issued rapidly increasing, there is more potential in developing successful trading strategies for IPOs. This Major Qualifying Project (MQP) uses characteristics of IPOs such as the greenshoe option in a combination with trading strategies for stocks in order to develop a strategy for trading IPOs. For this purpose the team used historical stock market data extracted from the TradeStation trading platform. An analysis of these data was made using a neural net program called Braincel. The program was used to form predictions on whether a stock's price would increase a certain level from an initial point. The predictions together with good money management resulted in a trading strategy with high potential.

  • 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.
Creator
Publisher
Identifier
  • E-project-101107-175726
Advisor
Year
  • 2007
Date created
  • 2007-10-11
Resource type
Major
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Last modified
  • 2021-02-02

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