Forecasting Corporate Bankruptcy Based on Managerial Overconfidence Using the Adaptive Neuro-Fuzzy Inference System

Abstract

This purpose of this study is to examine the relationship between managerial overconfidence and the prediction of bankruptcy and likelihood of the auditor's hesitation of the company‘s going concern over the financially distressed companies listed on the Indonesian Stock Exchange during 2014–2016. Managerial overconfidence is defined as the manager‘s excessive confidence that can be measured when the growth of the company‘s assets is higher than its sales growth. The financial condition is measured by the prediction of bankruptcy using the adaptive neuro-fuzzy inference system (ANFIS) model. The results showed that the likelihood of an auditor‘s hesitation of the company‘s going concerns is positively associated with managerial overconfidence in Indonesia because the auditor has a positive view on the ability of management. In addition, there is the likelihood that the auditor‘s hesitation of a company‘s going concerns is positively associated with the prediction of bankruptcy.