An Application of Hopfield Neural Network in Target Selection of Mergers and Acquisitions

Target selection is one of the most important steps of during the process of mergers and acquisitions. Hopfield neural network is very strong in pattern recognition which can simulate the criteria of acquirer and remind it. The network model overcomes the shortcomings of classic statistic and fuzzy models and embodies the requirements of acquirer. Demonstration shows that Hopfield network is an effective tool to choose targets with good performance if the standard of mergers and acquisition is feasible and reasonable.

[1]  Massimo Massa,et al.  Shareholder Investment Horizons and the Market for Corporate Control , 2005 .

[2]  B. Efron.  The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis , 1975 .

[3]  J. Harford.  What drives merger waves , 2005 .

[4]  Krishna G. Palepu,et al.  Predicting takeover targets: A methodological and empirical analysis , 1986 .

[5]  Christiano Lyra,et al.  Warm start by Hopfield neural networks for interior point methods , 2007, Comput. Oper. Res..

[6]  D. Stevens,et al.  Journal of Financial and Quantitative Analysis March 1973 FINANCIAL CHARACTERISTICS OF MERGED FIRMS: A MULTIVARIATE ANALYSIS , 2009 .

[7]  Qiang Zhang,et al.  Delay-dependent global stability condition for delayed Hopfield neural networks , 2007 .

[8]  Richard M. Walter.  The Usefulness of Current Cost Information for Identifying Takeover Targets and Earning Above-Average Stock Returns , 1994 .

[9]  Anne Carroll,et al.  Using Best's Ratings in Life Insurer Insolvency Prediction , 1994 .

[10]  S. Thompson.  Takeover activity among financial mutuals: An analysis of target characteristics , 1997 .

[11]  Joel Hasbrouck.  The characteristics of takeover targets and other measures , 1985 .

[12]  S. Mohamad,et al.  Exponential stability in Hopfield-type neural networks with impulses , 2007 .

[13]  Sergio Gómez,et al.  Portfolio selection using neural networks , 2005, Comput. Oper. Res..

[14]  George W. Ladd,et al.  Linear Probability Functions and Discriminant Functions , 1966 .

[15]  Eric Sorensen,et al.  An application of logit analysis to prediction of merger targets , 1984 .