Please use this identifier to cite or link to this item: https://utcc-dspacecris.eval.plus/handle/6626976254/212
Title: Comparison of Statistical and Linear Programming Approaches for Predicting Thai Listed Companies' Financial Problems
Authors: Lateh, Afifi 
Pasunon, Prasopchai 
Trakarnthalerngsak, Suda 
Nilkorn, Pranee 
Issue Date: 2008
Publisher: Chulalongkorn University Printing House
University of the Thai Chamber of Commerce
Source: 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.
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.
URI: https://scholar.utcc.ac.th/handle/6626976254/212
ISSN: 0125-2437
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.
Appears in Collections:JEO: Journal Articles

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