scholarly journals Comparing Logit, Probit and Multiple Discriminant Analysis Models in Predicting Bankruptcy of Companies

Author(s):  
Maryam Khalili Araghi ◽  
Sara Makvandi
2020 ◽  
Vol 110 (166) ◽  
pp. 31-76
Author(s):  
Paweł Kopczyński

Purpose: The main purpose of this article is to examine the usefulness of multiple discriminant analysis models in assessing the financial condition of individual enterprises, the state of the economy, and its sectors. The study assessed the financial situation of Polish listed companies at the end of the global economic crisis that started in 2007. Methodology/approach: Seven discriminant functions were used to assess the actual changes in the finan-cial situation of listed companies during the period of 2009–2014. In order to diagnose the end of the crisis, the period in which countries emerged from the global economic crisis was taken into account. The study covered 175 Polish companies listed on the regulated market operated by the Warsaw Stock Exchange, whose standalone financial statements were used. These companies belong to 22 sectors of the economy. It was assumed that the number of companies at risk of bankruptcy should have decreased during this period. Findings: The study showed that it is difficult to determine when the crisis ended and stopped affecting Polish listed companies. Their financial condition gradually improved during the period 2013–2014. Multiple discriminant analysis models are useful in assessing the risk of bankruptcy, but the study results show that it is safer to use several models simultaneously and to eliminate outliers. Research limitations/implications: The discriminant models used in the study are suitable for conducting research on large populations within enterprises and can be used by state and financial institutions (including banks) and authorities in Poland to facilitate the conduct of economic statistics, forecasting economic situation, etc. Originality/value: In Poland, many studies have been carried out on the usefulness of multiple discrimi-nant analysis models for the purposes of forecasting the bankruptcy of individual enterprises. However, there are few studies devoted to assessing the usefulness of the models in conducting research on large populations within enterprises (i.e., assessing the state of the economy and its sectors). This research helps to explore and fill this research gap.


1984 ◽  
Vol 23 (01) ◽  
pp. 15-22
Author(s):  
Y. Sekita ◽  
T. Ohta ◽  
M. Inoue ◽  
H. Takeda

SummaryJudgements of examinees’ health status by doctors and by the examinees themselves are compared applying multiple discriminant analysis. The doctors’ judgements of the examinees’ health status are studied comparatively using laboratory data and the examinees’ subjective symptom data.This data was obtained in an Automated Multiphasic Health Testing System. We discuss the health conditions which are significant for the judgement of doctors about the examinees. The results show that the explanatory power, when using subjective symptom data, is fair in the case of the doctors’ judgement. We found common variables, such as nervousness, lack of perseverance etc., which form the first canonical axis.


1990 ◽  
Vol 20 (1) ◽  
pp. 209-218 ◽  
Author(s):  
David Grayson ◽  
Keith Bridges ◽  
Diane Cook ◽  
David Goldberg

SYNOPSISIt is argued that latent trait analysis provides a way of examining the construct validity of diagnostic concepts which are used to categorize common mental illnesses. The present study adds two additional aspects of validity using multiple discriminant analysis applied to two widely used taxonomic systems. Scales of anxiety and depression derived from previous latent trait analyses are applied to individuals reaching criteria for ‘caseness’ on the ID-CATEGO system and the DSM-III system, both at initial diagnosis and six months later. The first multiple discriminant analysis is carried out on the initial scale scores, and the results are interpreted in terms of concurrent validity. The second analysis uses improvement scores on the two scales and relates to predictive validity. It is argued that the ID-CATEGO system provides a better classification for common mental illnesses than the DSM-III system, since it allows a better discrimination to be made between anxiety and depressive disorders.


Sign in / Sign up

Export Citation Format

Share Document