Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm

Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm

This paper provides operational guidance for validating Naïve Bayes model for bankruptcy prediction. First, researcher suggests heuristic methods that guide the selection of bankruptcy potential variables. Correlations analyses were used to eliminate variables that provide little or no additional in...

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Main Author: Muhammad Zuhairi, Abd Hamid
Format: Thesis
Language:eng
eng
Published: 2014
Subjects:
HG Finance
T Technology (General)
Online Access:https://etd.uum.edu.my/4708/1/s812905.pdf
https://etd.uum.edu.my/4708/2/s812905_abstract.pdf
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id my-uum-etd.4708
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Hanafi, Norshafizah
topic HG Finance
T Technology (General)
spellingShingle HG Finance
T Technology (General)
Muhammad Zuhairi, Abd Hamid
Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
description This paper provides operational guidance for validating Naïve Bayes model for bankruptcy prediction. First, researcher suggests heuristic methods that guide the selection of bankruptcy potential variables. Correlations analyses were used to eliminate variables that provide little or no additional information beyond that subsumed by the remaining variables. A Naïve Bayes model was developed using the proposed heuristic method and it performed well based on logistic regression, which is used for validation analysis. The developed Naïve Bayes model consists of three first-order variables and seven second-order variables. The results show that the model's performance is best when the method of enter is used in logistic regression which is percentage of correct is 90%. Finally, the results of this study could also be applicable to businesses and investors in decision making, besides validating bankruptcy prediction.
format Thesis
qualification_name masters
qualification_level Master's degree
author Muhammad Zuhairi, Abd Hamid
author_facet Muhammad Zuhairi, Abd Hamid
author_sort Muhammad Zuhairi, Abd Hamid
title Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
title_short Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
title_full Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
title_fullStr Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
title_full_unstemmed Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm
title_sort validating bankruptcy prediction by using bayesian network model: a case from malaysian firm
granting_institution Universiti Utara Malaysia
granting_department Othman Yeop Abdullah Graduate School of Business
publishDate 2014
url https://etd.uum.edu.my/4708/1/s812905.pdf
https://etd.uum.edu.my/4708/2/s812905_abstract.pdf
_version_ 1747827785245655040
spelling my-uum-etd.47082022-08-03T01:59:38Z Validating bankruptcy prediction by using Bayesian network model: A case from Malaysian firm 2014 Muhammad Zuhairi, Abd Hamid Hanafi, Norshafizah Othman Yeop Abdullah Graduate School of Business Othman Yeop Abdullah Graduate School of Business HG Finance T Technology (General) This paper provides operational guidance for validating Naïve Bayes model for bankruptcy prediction. First, researcher suggests heuristic methods that guide the selection of bankruptcy potential variables. Correlations analyses were used to eliminate variables that provide little or no additional information beyond that subsumed by the remaining variables. A Naïve Bayes model was developed using the proposed heuristic method and it performed well based on logistic regression, which is used for validation analysis. The developed Naïve Bayes model consists of three first-order variables and seven second-order variables. The results show that the model's performance is best when the method of enter is used in logistic regression which is percentage of correct is 90%. Finally, the results of this study could also be applicable to businesses and investors in decision making, besides validating bankruptcy prediction. 2014 Thesis https://etd.uum.edu.my/4708/ https://etd.uum.edu.my/4708/1/s812905.pdf text eng public https://etd.uum.edu.my/4708/2/s812905_abstract.pdf text eng public masters masters Universiti Utara Malaysia Ahn, H & Kim, K.J. (2009). Bankruptcy Prediction Modeling with Hybrid Case-Based Reasoning and Genetic Algorithms Approach. Applied Soft Computing 9, Pp 599-607. Altman, Edward I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, Pp. 589-609. Beaver, William, H., (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, Supplement, Empirical Research in Accounting: Selected Studies, pp. 71-111. 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