An application of rank transformation : merger target predictions
An application of rank transformation : merger target predictions
Files (excerpt)
Published date
2006
Resource type
Publisher
Assumption University
ISBN
ISSN
DOI
Call no.
Other identifier(s)
Edition
Copyrighted date
Language
eng
File type
application/pdf
Extent
Other title(s)
Advisor
Other Contributor(s)
Assumption University. Martin de Tours School of Management and Economics
Citation
AU Journal of management 4, 1 (January-June 2006), 33-42
Degree name
Degree level
Degree discipline
Degree department
Degree grantor
Abstract
This study attempts to predict merger targets among banks, and also investigates the predictive
power rank transformation adds to the prediction models. Rank transformation has been suggested as
a robust and powerful tool for financial problems. Multiple· discriminant analysis (MDA) and logistic
regression have been applied to selected ranked and unranked financial ratios. Then, the classification
results of MDA and logistic regression on both ranked and unranked data sets are compared. The
results have indicated that rank transformation does improve the predictive power of MDA and logistic
regression.
Table of contents
Description
In English ; only abstract in English.
punsarn.dc.description.sponsorship
Spatial Coverage
Rights
This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.