Predicting corporate failure in the UK: A multidimensional scaling approach
Predicting corporate failure in the UK: A multidimensional scaling approach
Scaling techniques are proposed as an alternative tool for the analysis and prediction of corporate failure. This approach has the advantage of reproducing the main features of the data in the form of statistical maps that lend themselves to intuitive interpretation. The maps are further analysed by means of standard multivariate statistical tools. The methodology is demonstrated using a recent sample of UK industrial companies. A future-dated holdout sample is also employed to illustrate how the Multidimensional Scaling technique can aid practitioners when assessing the financial health of a company.
University of Southampton
Neophytou, Evridiki
4abc440a-2043-49a9-958e-a6374ce50c97
Mar Molinero, Cecilio
5892dc03-ff85-4697-b196-a5925ae53805
2001
Neophytou, Evridiki
4abc440a-2043-49a9-958e-a6374ce50c97
Mar Molinero, Cecilio
5892dc03-ff85-4697-b196-a5925ae53805
Neophytou, Evridiki and Mar Molinero, Cecilio
(2001)
Predicting corporate failure in the UK: A multidimensional scaling approach
(Discussion Papers in Accounting and Management Science, 01-172)
Southampton, UK.
University of Southampton
23pp.
Record type:
Monograph
(Discussion Paper)
Abstract
Scaling techniques are proposed as an alternative tool for the analysis and prediction of corporate failure. This approach has the advantage of reproducing the main features of the data in the form of statistical maps that lend themselves to intuitive interpretation. The maps are further analysed by means of standard multivariate statistical tools. The methodology is demonstrated using a recent sample of UK industrial companies. A future-dated holdout sample is also employed to illustrate how the Multidimensional Scaling technique can aid practitioners when assessing the financial health of a company.
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Published date: 2001
Identifiers
Local EPrints ID: 35733
URI: http://eprints.soton.ac.uk/id/eprint/35733
ISSN: 1356-3548
PURE UUID: 86baa224-9959-4b1b-b057-aed8703ab9f0
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Date deposited: 25 May 2006
Last modified: 15 Mar 2024 07:54
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Contributors
Author:
Evridiki Neophytou
Author:
Cecilio Mar Molinero
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