Applied Optimization

By: Constantin Zopounidis, Dimitra Paraschou

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Hardcover | 31 January 1998

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204 Pages

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25.4 x 16.51 x 1.91

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This book provides a new point of view on the subject of business failure prediction, through the application of multicriteria analysis methods. The aim of the book is to provide a review of the research in the area and to explore the adequacy of these methods to one of the most complex problems in the area of financial management. In addition, the book explores the applications of the methods so that it can become a very useful tool for researchers and practitioners. The analysis of the modeling and the results in these applications provides the background for further employment of the methods.

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Published: 7th December 2010

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Aknowledgments	p. ix
Table of Contents	p. xi
List of Tables	p. xv
List of Figures	p. xix
Prologue	p. xxi
Business Failure Research: Some Statistics, Methods, Models and Variables	p. 1
Introduction	p. 1
Methods and models	p. 6
Univariate statistical methods	p. 7
Discriminant analysis	p. 8
Linear probability model	p. 12
Logit and probit analyses	p. 13
Recursive partitioning algorithm	p. 16
Survival Analysis	p. 19
Expert Systems	p. 21
Neural Networks	p. 22
Financial ratios and other characteristics	p. 24
Conclusions	p. 30
Multicriteria Decision Aid Methodology	p. 31
Introduction	p. 31
Multiobjective Mathematical Programming	p. 33
Multiobjective Mathematical Programming for bankruptcy prediction	p. 34
Multiattribute Utility Theory	p. 38
Outranking Relations Approach	p. 39
Preference Disaggregation Approach	p. 41
Multicriteria Analysis and Business Failure	p. 42
Electre Tri Method and Business Failure Prediction	p. 45
Introduction	p. 45
Electre Tri	p. 46
The study of Dimitras, Zopounidis and Hurson (1995)	p. 53
Sample and data	p. 53
Classification Results	p. 55
The study of Dimitras (1995)	p. 60
Sample and data	p. 60
Classification Results	p. 61
Comparison between Electre Tri and discriminant analysis	p. 66
Concluding remarks	p. 67
Rough Sets and Business Failure Prediction	p. 69
Introduction	p. 69
Information table and indiscernibility relation	p. 69
Approximation of sets	p. 70
Reduction and dependency of attributes	p. 71
Decision rules	p. 72
Decision support using decision rules	p. 73
Valued closeness relation (VCR)	p. 74
The study of Slowinski and Zopounidis (1995)	p. 77
Sample and data	p. 77
Application	p. 78
The study of Dimitras, Slowinski, Susmaga, and Zopounidis (1997)	p. 89
Sample and data	p. 89
Application	p. 89
Comparison of the rough set approach with the discriminant analysis	p. 99
Comparison of the rough set approach with the logit analysis	p. 103
The study of Greco, Matarazzo and Slowinski (1997)	p. 106
Sample and data	p. 110
Application	p. 111
Concluding remarks	p. 116
Preference Disaggregation Method and Business Failure Prediction	p. 117
Introduction	p. 117
The UTA Method	p. 117
The study of Zopounidis (1987) - The MINORA System	p. 119
First step	p. 126
Second Step	p. 129
Third step	p. 130
Fourth step	p. 131
The study of Zopounidis and Doumpos (1997) - The UTADIS method	p. 135
The UTADIS method	p. 135
Sample and data	p. 139
Classification results	p. 142
Comparison between UTADIS and Discriminant Analysis	p. 143
Concluding remarks	p. 145
Conclusions	p. 147
References	p. 151
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Applied Optimization

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Hardcover

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