Abstract

http://ssrn.com/abstract=1080430
 
 

Citations (2)



 


 



Insolvency Prediction Model Using Multivariate Discriminant Analysis and Artificial Neural Network for the Finance Industry in New Zealand


Kim Choy Chung


KIMEP

Shin Shin Tan


Polson Higgs

David K. Holdsworth


University of Otago


International Journal of Business and Management, Vol. 39, No. 1, pp. 19-28, 2008

Abstract:     
Models of insolvency are important for managers who may not appreciate how serious the financial health of their company is becoming until it is too late to take effective action. Multivariate discriminant analysis and artificial neural network are utilized in this study to create an insolvency predictive model that could effectively predict any future failure of a finance company and validated in New Zealand. Financial ratios obtained from corporate balance sheets are used as independent variables while failed/non-failed company is the dependent variable. The results indicate the financial ratios of failed companies differ significantly from non-failed companies. Failed companies were also less profitable and less liquid and had higher leverage ratios and lower quality assets.

Number of Pages in PDF File: 10

Keywords: Corporate insolvency, financial ratios, multivariate discriminant analysis, artificial neural networks

JEL Classification: G33, M41, M47

Accepted Paper Series





Download This Paper

Date posted: January 3, 2008  

Suggested Citation

Chung, Kim Choy and Tan, Shin Shin and Holdsworth, David K., Insolvency Prediction Model Using Multivariate Discriminant Analysis and Artificial Neural Network for the Finance Industry in New Zealand. International Journal of Business and Management, Vol. 39, No. 1, pp. 19-28, 2008. Available at SSRN: http://ssrn.com/abstract=1080430

Contact Information

Kim Choy Chung (Contact Author)
KIMEP ( email )
Almaty
Kazakhstan
Shin Shin Tan
Polson Higgs ( email )
139 Moray place
Dunedin
New Zealand
David K. Holdsworth
University of Otago ( email )
P.O. Box 56
Dunedin, Otago
New Zealand
Feedback to SSRN


Paper statistics
Abstract Views: 2,933
Downloads: 827
Download Rank: 15,253
Citations:  2
People who downloaded this paper also downloaded:
1. Forecasting Stock Market with Neural Networks
By Tsong-wuu Lin and Chan-chien Yu

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo8 in 0.406 seconds