Abstract

http://ssrn.com/abstract=7560
 
 

Citations



 


 



Predicting the Fate of Insolvent Companies in Administrative Receivership - Using Statistical and Neural Classification Methods


Robert Hamilton


Loughborough University - Business School

J. Barry Howcroft


Loughborough University - Business School

Keith Pond


Loughborough University - Business School

Zhonghua Liu


Jiangsu TV University at Nanjing, China

December 1995

Loughborough University Banking Centre Research Series 95/1995

Abstract:     
The paper focuses upon businesses which are in crisis and attempts to assess whether financial variables can be identified and used to discriminate between insolvent companies which can be rescued and those which cannot. In attempting to resolve this question, the research utilises a sample of companies placed into administrative receivership and applies four classification techniques: two statistical methods - Linear Discriminant Analysis and Logistic Regression; and two neural nets - the Backpropagation net and the Learning Vector Quantization net. The performance of the four different classification procedures was quite comparable and revealed estimated classification rates of between 70 - 80%. The analysis also identified six discriminating variables, but three of these - debtor turnover, gearing ratio and current ratio - were particularly important in predicting outcomes.

JEL Classification: C25, C88, G21, G88, G38

working papers series





Not Available For Download

Date posted: June 3, 1998  

Suggested Citation

Hamilton, Robert and Howcroft, J. Barry and Pond, Keith and Liu, Zhonghua, Predicting the Fate of Insolvent Companies in Administrative Receivership - Using Statistical and Neural Classification Methods (December 1995). Loughborough University Banking Centre Research Series 95/1995. Available at SSRN: http://ssrn.com/abstract=7560

Contact Information

Robert Hamilton
Loughborough University - Business School ( email )
Ashby Road
Loughborough
Nottingham NG1 4BU, LE11 3TU
Great Britain
J. Barry Howcroft
Loughborough University - Business School ( email )
Ashby Road
Loughborough
Nottingham NG1 4BU, LE11 3TU
Great Britain
Keith Pond (Contact Author)
Loughborough University - Business School ( email )
Ashby Road
Loughborough Banking Centre
Leicestershire LE11
United Kingdom
+44 1509 223290 (Phone)
+44 1509 223962 (Fax)
Zhonghua Liu
Jiangsu TV University at Nanjing, China
Nanjing
China
Feedback to SSRN


Paper statistics
Abstract Views: 888

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo5 in 0.594 seconds