Neural network models for initial public offerings

Steven J. Robertson, Bruce L. Golden, George Runger, Edward A. Wasil

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

In this article, we construct models that predict the first-day return of an initial public offering. Our data set consists of the first-day returns for 1075 firms that went public between 1989 and 1994 and information that we gathered on 16 predictor variables. We segment the data set into technology and nontechnology offerings and construct three types of models for each segment - a regression model and two neural network models. Factorial experiments are used to construct the neural network models. We find that the neural network models perform well on both types of offerings.

Original languageEnglish (US)
Pages (from-to)165-182
Number of pages18
JournalNeurocomputing
Volume18
Issue number1-3
DOIs
StatePublished - Jan 1998

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Keywords

  • Artificial neural networks
  • Backpropagation
  • Comparison with ordinary least squares
  • Initial public offerings

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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