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Comparison of Statistical and Linear Programming Approaches for Predicting Thai Listed Companies' Financial Problems
Journal
University of the Thai Chamber of Commerce Journal
Publisher(s)
Chulalongkorn University Printing House
University of the Thai Chamber of Commerce
Date Issued
2008
Other Contributor(s)
University of the Thai Chamber of Commerce. Journal Editorial Office
Abstract
The objective of this research is to compare four discriminant models FLDF: Fisher's Linear Discriminant Function, LRA: Logistic Regression Analysis, MSD (Freed and Glover, 1986), and LCM (Lam, Choo, and Moy, 1996) for two-group discriminant analysis. The data were financial ratios of 210 Thai listed companies collected during 2536-2539 B.C., 30 bankrupts and 180 non-bankrupts. The performance of each model was assessed by correct classification and prediction accuracy. The result is the LRA model performed best, followed by the MSD and LCM models respectively. In terms of prediction accuracy, the LCM model performed best, followed by the LRA and MSD models respectively.
Subject(s)
ISSN
0125-2437
Access Rights
public
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.
Rights Holder(s)
University of the Thai Chamber of Commerce
Bibliographic Citation
Afifi Lateh, Prasopchai Pasunon, Suda Trakarnthalerngsak, Pranee Nilkorn (2008) Comparison of Statistical and Linear Programming Approaches for Predicting Thai Listed Companies' Financial Problems. University of the Thai Chamber of Commerce Journal Vol.28 No.1.
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