Project Type MQP Submission date 2007-10-11 Authors Diana Damyanova Damyanova, EC Esra Unluaslan, EC URN E-project-101107-175726 Title Neural Net-Based Software for Trading Initial Public Offerings Advisor Radzicki, Michael J, SS Availability unrestricted Abstract
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.
Files Neural_Net_Based_Software_for_Trading_Initial_Public_Offerings.pdf
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