Predicting IPO underpricing with genetic algorithms Articles uri icon

publication date

  • marzo 2012

start page

  • 133

end page

  • 146

issue

  • S12

volume

  • 8

international standard serial number (ISSN)

  • 0974-0635

abstract

  • This paper introduces a rule system to predict first-day returns of initial public offerings based on the structure of the offerings. The solution is based on a genetic algorithm using a Michigan approach. The performance of the system is assessed comparing it to a set of widely used machine learning algorithms. The results suggest that this approach offers significant advantages on two fronts: predictive performance and robustness to outlier patterns. The importance of the latter should be emphasized as the results in this domain are very sensitive to their presence.

keywords

  • Genetic algorithm
    IPO
    Underpricing