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A revision of Altman z-score model in financial distress prediction of listed companies in Vietnam

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Resumo:The primary purpose of this report is to evaluate and improve the accuracy of Altman's Z-score model in financial distress prediction of listed companies in Vietnam. Identifying new cut off scores to the prediction models is necessary to adapt to the characteristics of the Vietnamese market. The study implements multiple discriminant analysis as a crucial methodology to calibrate the Z-score model with 51 forced delisted companies and 51 non-delisted companies. The Z new model achieves a one-year accuracy rate of 91.58% in forecasting financial distress for Vietnamese companies. The study shows that the superiority of the Altman Z-score model in financial distress prediction is not in the Z-score but in the methodology in which the model is built and put into practice.
Autores principais:Tran, Duc Anh
Assunto:Financial distress Altman z score model Financial ratios Multiple discriminant analysis Prediction model Vietnam
Ano:2022
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:The primary purpose of this report is to evaluate and improve the accuracy of Altman's Z-score model in financial distress prediction of listed companies in Vietnam. Identifying new cut off scores to the prediction models is necessary to adapt to the characteristics of the Vietnamese market. The study implements multiple discriminant analysis as a crucial methodology to calibrate the Z-score model with 51 forced delisted companies and 51 non-delisted companies. The Z new model achieves a one-year accuracy rate of 91.58% in forecasting financial distress for Vietnamese companies. The study shows that the superiority of the Altman Z-score model in financial distress prediction is not in the Z-score but in the methodology in which the model is built and put into practice.