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

DOI

10.2991/assehr.k.200331.149How to use a DOI?

Keywords

auditor, managerial overconfidence, forecasting, corporate, bankruptcy, going concern, adaptive neuro-fuzzy inference system, ANFIS

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.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yulius Eka Agung Seputra
PY  - 2020
DA  - 2020/04/03
TI  - Forecasting Corporate Bankruptcy Based on Managerial Overconfidence Using the Adaptive Neuro-Fuzzy Inference System
BT  - Proceedings of the 3rd International Conference on Vocational Higher Education (ICVHE 2018)
PB  - Atlantis Press
SP  - 245
EP  - 255
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200331.149
DO  - 10.2991/assehr.k.200331.149
ID  - Seputra2020
ER  -