Comparative evaluation of multi layer perceptrons, to hybrid multi layer perceptrons, with multicriteria hierarchical discrimination and logistic regression in corporate financial analysis

Authors:
N. Loukeris
Affiliations:
C.C.F.E.A., University of Essex, Chania, Crete, Greece, United Kingdom
Venue:
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Year:
2007

Citing 4
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Abstract

The net present value of corporations is reflected in the stock price, leading portfolio mangers to maximize their assets, securing stockholders interests. Extended accounting data produced by accounting reports, and financial markets include lucrative hidden information. Econometrics, Neural Networks and Multicriteria Analysis classify companies describing their economic robustness. In a detailed comparison Multi Layer Perceptron classification is compared to neuro-genetic hybrid of Multi Layer Perceptron, Logistic Regressions and Multigroup Hierarchical Discrimination classifications to determine efficient methods in Financial Analysis. Simple Logistic and Logistic Model Trees methods had a fine performance.