Abstract
The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO–NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO–CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO–SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).
Highlights
Business bankruptcy has caused a huge loss of wealth on the part of investors
The high association between going concern doubts (GCD) and business bankruptcy has been verified by past studies (Behn et al 2001; Geiger and Rama 2003; Koh and Low 2004; Martens et al 2008; Mokhatab et al 2011; Yeh et al 2014)
The purpose of this study is to develop a satisfactory model for forecasting the GCD of firms and to forecast an omen for such GCD and to reduce damage to both investors and auditors
Summary
Building a valid going concern problem forecast model for an enterprise has become an important goal for both academics and financial practitioners. The high association between going concern doubts (GCD) and business bankruptcy has been verified by past studies (Behn et al 2001; Geiger and Rama 2003; Koh and Low 2004; Martens et al 2008; Mokhatab et al 2011; Yeh et al 2014). The Statement of Auditing Standard (SAS) demands that when an auditor suspects the auditee’s capability of going concern, the auditor should conduct the necessary and reasonable auditing processes required to examine the auditee’s related financial information. If an auditor makes a misjudgment during the auditing process and issues an incorrect audit report, this has important consequences (e.g. business crisis or investment losses). The question of how to help auditors notice signs of going concern is an important one
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