Prediction of financial information manipulation by using support vector machine and probabilistic neural network

被引：17

作者：

Ogut, Hulisi ^{[1
]}

Aktas, Ramazan ^{[1
]}

Alp, Ali ^{[1
]}

Doganay, M. Mete ^{[2
]}

机构：

[1] TOBB Univ Econ & Technol, Dept Business Adm, TR-06560 Ankara, Turkey

[2] Cankaya Univ, Dept Business Adm, TR-06530 Ankara, Turkey

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 03期

关键词：

Financial information manipulation; Support vector machine; Probabilistic neural network; EARNINGS MANAGEMENT; KERNEL; FIRMS;

D O I：

10.1016/j.eswa.2008.06.055

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Different methods have been used to predict financial information manipulation that can be defined as the distortion of the information in the financial statements. The purpose of this paper is to predict financial information manipulation by using support vector machine (SVM) and probabilistic neural network (PNN). A number of financial ratios are used as explanatory variables. Test performance of classification accuracy, sensitivity and specificity statistics for PNN and SVM are compared with the results of discriminant analysis, logistics regression (logit), and probit classifiers, which have been used in other studies. We have found that the performance of SVM and PNN are higher than that of the other classifiers analyzed before. Thus, both classifiers can be used as automated decision support system for the detection of financial information manipulation. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：5419 / 5423

页数：5

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