Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies

Introduction: in 1968, Altman developed a multivariable predictive Z-score model to assess the probability of a public manufacturing company going to bankruptcy based on financial ratios. Later, Altman (1983) re-stated a more improved Z’’-Score model designed to apply in public or private, manufact...

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Autores principales:	Martín P. Pantoja Aguilar, Guadalupe de Montserrat Pizano Ramírez, Berenice Lerma Torres, Miguel Ángel Zavala Vargas
Formato:	article
Lenguaje:	EN ES
Publicado:	Universidad De La Salle Bajío 2021
Materias:	bankruptcy prediction Z’’-Score ratios financial distress model accuracy emerging countries Science Q Science (General) Q1-390 Social Sciences H Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/1ddf968fd73242af836e333a1815d637
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spelling	oai:doaj.org-article:1ddf968fd73242af836e333a1815d6372021-11-11T15:04:14ZTesting Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies10.21640/ns.v13i27.28812007-0705https://doaj.org/article/1ddf968fd73242af836e333a1815d6372021-11-01T00:00:00Zhttp://novascientia.delasalle.edu.mx/ojs/index.php/Nova/article/view/2881https://doaj.org/toc/2007-0705 Introduction: in 1968, Altman developed a multivariable predictive Z-score model to assess the probability of a public manufacturing company going to bankruptcy based on financial ratios. Later, Altman (1983) re-stated a more improved Z’’-Score model designed to apply in public or private, manufacturing, or non-manufacturing firms, but also in emerging countries. Prediction of the updated model proved to be highly efficient. This research was conducted to prove the level of accuracy of the Z’’-Score model applied to firms listed in the Mexican Stock Exchange (MSE) since there is little relevant research on this subject. Method: this research was conducted under a quantitative approach as a census and its scope was situational with a non-experimental and longitudinal research design. The period covered by this research was 2012-2019 since the data was available for those years under a somehow stable economic situation without significant economic ups and downs. This research considered the integration of a large financial database and the design of a typology to classify and analyze 155 firms based on a standard deviation and average results of 837 Z’’-scores. A second analysis was conducted to prove if the predicted situation (area) by the Z’’-Score corresponded to the real situation in the marketplace for every company. Results: the results showed that the accuracy level of the Altman model decreased when applied to Mexican firms. The error of the model applied to Mexican companies related to those classified in the bankruptcy prediction area was 75 % of misclassification cases. The total error of the model included all areas, or cases, was 18 % of misclassification cases. This model is supposed to be effective within a time frame of two years before a possible bankruptcy. Even considering a longer time frame, the companies located in the bankruptcy prediction area continued having misclassifications representing 57 % of error. The error for the model considering all cases and all areas, was 14 % of misclassification cases. This represented a high level of inefficiency of the model applied to an emerging country companies, such as Mexico. Discussion or conclusion: the model is certainly effective while predicting companies in the areas of non-bankrupt sector and grey, but it was inefficient when predicting the possibility of bankruptcy. It was also demonstrated that the time frame of two years is no longer effective when applying the model to Mexican companies. As a result, more research cases are needed to update the model to perform efficiently in emerging countries including country-specific conditions and considering a different time frame to predict bankruptcy. Martín P. Pantoja AguilarGuadalupe de Montserrat Pizano RamírezBerenice Lerma TorresMiguel Ángel Zavala VargasUniversidad De La Salle Bajíoarticlebankruptcy predictionZ’’-Scoreratiosfinancial distressmodel accuracyemerging countriesScienceQScience (General)Q1-390Social SciencesHSocial sciences (General)H1-99ENESNova Scientia, Vol 13, Iss 27 (2021)
institution	DOAJ
collection	DOAJ
language	EN ES
topic	bankruptcy prediction Z’’-Score ratios financial distress model accuracy emerging countries Science Q Science (General) Q1-390 Social Sciences H Social sciences (General) H1-99
spellingShingle	bankruptcy prediction Z’’-Score ratios financial distress model accuracy emerging countries Science Q Science (General) Q1-390 Social Sciences H Social sciences (General) H1-99 Martín P. Pantoja Aguilar Guadalupe de Montserrat Pizano Ramírez Berenice Lerma Torres Miguel Ángel Zavala Vargas Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
description	Introduction: in 1968, Altman developed a multivariable predictive Z-score model to assess the probability of a public manufacturing company going to bankruptcy based on financial ratios. Later, Altman (1983) re-stated a more improved Z’’-Score model designed to apply in public or private, manufacturing, or non-manufacturing firms, but also in emerging countries. Prediction of the updated model proved to be highly efficient. This research was conducted to prove the level of accuracy of the Z’’-Score model applied to firms listed in the Mexican Stock Exchange (MSE) since there is little relevant research on this subject. Method: this research was conducted under a quantitative approach as a census and its scope was situational with a non-experimental and longitudinal research design. The period covered by this research was 2012-2019 since the data was available for those years under a somehow stable economic situation without significant economic ups and downs. This research considered the integration of a large financial database and the design of a typology to classify and analyze 155 firms based on a standard deviation and average results of 837 Z’’-scores. A second analysis was conducted to prove if the predicted situation (area) by the Z’’-Score corresponded to the real situation in the marketplace for every company. Results: the results showed that the accuracy level of the Altman model decreased when applied to Mexican firms. The error of the model applied to Mexican companies related to those classified in the bankruptcy prediction area was 75 % of misclassification cases. The total error of the model included all areas, or cases, was 18 % of misclassification cases. This model is supposed to be effective within a time frame of two years before a possible bankruptcy. Even considering a longer time frame, the companies located in the bankruptcy prediction area continued having misclassifications representing 57 % of error. The error for the model considering all cases and all areas, was 14 % of misclassification cases. This represented a high level of inefficiency of the model applied to an emerging country companies, such as Mexico. Discussion or conclusion: the model is certainly effective while predicting companies in the areas of non-bankrupt sector and grey, but it was inefficient when predicting the possibility of bankruptcy. It was also demonstrated that the time frame of two years is no longer effective when applying the model to Mexican companies. As a result, more research cases are needed to update the model to perform efficiently in emerging countries including country-specific conditions and considering a different time frame to predict bankruptcy.
format	article
author	Martín P. Pantoja Aguilar Guadalupe de Montserrat Pizano Ramírez Berenice Lerma Torres Miguel Ángel Zavala Vargas
author_facet	Martín P. Pantoja Aguilar Guadalupe de Montserrat Pizano Ramírez Berenice Lerma Torres Miguel Ángel Zavala Vargas
author_sort	Martín P. Pantoja Aguilar
title	Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
title_short	Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
title_full	Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
title_fullStr	Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
title_full_unstemmed	Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies
title_sort	testing altman’s z’’-score to assess the level of accuracy of the model in mexican companies
publisher	Universidad De La Salle Bajío
publishDate	2021
url	https://doaj.org/article/1ddf968fd73242af836e333a1815d637
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Testing Altman’s Z’’-Score to assess the level of accuracy of the model in Mexican companies

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