EconPapers    
Economics at your fingertips  
 

Evaluation of the going‐concern status for companies: An ensemble framework‐based model

Yu‐Feng Hsu and Wei‐Po Lee

Journal of Forecasting, 2020, vol. 39, issue 4, 687-706

Abstract: Issuing a going‐concern opinion is a difficult and complex task for auditors. The auditors have to take into account different critical factors in order to make the right decision based on information obtained from the auditing process. This study adopts the so‐called “random forest” approach (based on the ensemble method) to assist auditors in making such a decision. To investigate the corresponding effect of the proposed approach, we conduct a series of experiments and a performance comparison. The results show that the random forest method outperforms the baseline methods in terms of the accuracy rate, ROC area, kappa value, type II error, precision, and recall rate. The proposed approach is proven to be more accurate and stable than previous methods.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/for.2653

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:39:y:2020:i:4:p:687-706

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:jforec:v:39:y:2020:i:4:p:687-706