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Explaining qualifications in audit reports using a support vector machine methodology

Pasiouras Fotios, Chrysovalantis Gaganis, Michael Doumpos

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/B6596A66-239C-43BE-A49F-1DA410F91FBC-
Αναγνωριστικόhttps://doi.org/10.1002/isaf.v13:4-
Γλώσσαen-
ΤίτλοςExplaining qualifications in audit reports using a support vector machine methodologyen
ΔημιουργόςPasiouras Fotiosen
ΔημιουργόςΠασιουρας Φωτιοςel
ΔημιουργόςChrysovalantis Gaganisen
ΔημιουργόςMichael Doumposen
ΕκδότηςAssociation for Computing Machineryen
ΠερίληψηThe verification of whether the financial statements of a firm represent its actual position is of major importance for auditors, who should provide a qualified report if they conclude that the financial statements fail to meet this requirement. This paper implements support vector machines (SVMs) to develop models that may support auditors in this task. Linear and non-linear models are developed and their performance is analysed using training samples of different size and out-of-sample/out-of-time data. The results show that all SVM models are capable of distinguishing between qualified and unqualified financial statements with satisfactory accuracy. The performance of the models over time is also explored. Copyright © 2005 John Wiley & Sons, Ltd.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-25-
Ημερομηνία Δημοσίευσης2005-
Βιβλιογραφική ΑναφοράDoumpos M, Gaganis C, Pasiouras F., "Explaining qualifications in audit reports using a support vector machine methodology". Int. Syst. in Accounting, Finance and Management, Vol. 13, no. 4 , pp. 197-215, Dec. 2005.doi: 10.1002/isaf.268.en

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