Title: Bankruptcy prediction using auditor size and auditor opinion

Authors: Chrysovalantis Gaganis, Pavlos Sochos, Constantin Zopounidis

Addresses: Department of Economics, University of Crete, Greece; Financial Engineering Laboratory, Department of Production Engineering and Management, Technical University of Crete, Greece. ' Financial Engineering Laboratory, Department of Production Engineering and Management, Technical University of Crete, Greece. ' Financial Engineering Laboratory, Department of Production Engineering and Management, Technical University of Crete, Greece

Abstract: In the present study, we investigate the explanatory power of information such as auditors| opinion and auditors| size in predicting impending bankruptcy for companies operating in the Greek market. Using nine financial ratios and two dummy variables, covering all dimensions of firms| financial performance, we initially develop two classification technique based models, Artificial Neural Networks (ANN) and Discriminant Analysis (DA). Our main purpose is to find out if the integration of the variables of audit opinion and auditor size in the initial models increases their ability in predicting impending bankruptcy. A comparison of the prediction accuracy of these two models before and after the integration of the additional informational variables is also included. The results indicate that both models achieve more satisfactory classification accuracy in discriminating bankrupted and non-bankrupted firms when the variables of audit opinion, auditors| are incorporated in the analysis compared to the use of financial ratios, only.

Keywords: bankruptcy prediction; Greece; auditors; artificial neural networks; ANNs; discriminant analysis; auditor size; auditor opinion.

DOI: 10.1504/IJFSM.2010.034553

International Journal of Financial Services Management, 2010 Vol.4 No.3, pp.220 - 238

Published online: 07 Aug 2010 *

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