Name
Abstract | ||
|---|---|---|
This paper presents a new approach to forecast the acquisition of a firm in Greece based on the rough set theory. A sample of acquired firms and a sample of equivalent non-acquired firms are considered and the objective is to create patterns which would be able to distinguish between the two classes of firms, based upon differences in their financial characteristics (financial ratios). For this purpose, the rough set approach is used. The information about the firms is organized in a financial information table. In this table, financial characteristics of the firms correspond to condition attributes and the classification is defined by a decision attribute telling if a firm has been acquired or not. The rough set approach enables one to discover minimal subsets of condition attributes (financial ratios) ensuring an acceptable approximation of the classification of the firms analyzed and to derive decision rules from the financial information table which can be used to best distinguish in the future between acquired and non-acquired firms. A comparison of the rough set approach with the discriminant analysis on the same set of data shows an advantage of the new approach. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1016/S0377-2217(96)00110-5 | European Journal of Operational Research |
Keywords | Field | DocType |
Decision,Finance,Rough set theory,Classification,Prediction,Company acquisition | Decision rule,Financial ratio,Data mining,Financial information,Rough set,Artificial intelligence,Linear discriminant analysis,Dominance-based rough set approach,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
100 | 1 | 0377-2217 |
Citations | PageRank | References |
41 | 6.30 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roman Slowinski | 1 | 5561 | 516.06 |
| Constantin Zopounidis | 2 | 1066 | 90.47 |
| A. I. Dimitras | 3 | 189 | 19.97 |