Acceso usuarios
, Mário A. Guerreiro Antão, Catarina Carvalho Peres Terrinca, João Manuel Afonso Geraldes
Purpose: validate, in the existing models, its effectiveness and ability to provide useful information for decision-making, allowing the choice of one that presented as the best alternative for predicting bankruptcy for companies in the transport economic sector (NACE H) up to 6 years before it occurs.
Theoretical Framework: in the last decades, since Beaver's (1966) preliminary work in bankruptcy prediction, followed by Altman (1968) models, numerous authors developed different techniques and models to this purpose. Of all the techniques used and developed in almost 60 years of bankruptcy prediction study, Multivariate Discriminant Analysis (MDA) stands out. Despite its limitations, it best combines management and usage simplicity offering stable levels of efficiency.
Design/Methodology/Approach: we selected, Portuguese and Spanish companies, from the transport and storage economic sector, subject to statutory auditing, in a sample of 22 companies, considered healthy, according to the most common criterion in the literature: Equity above zero, during six and that in the seventh were considered bankrupt (Equity below zero) and another, paired with the previous one, by Total Assets and Revenues, with 36 companies that presented Equity above zero throughout all the analyzed period, granting the analyzed models full forecasting potential. Were used 21 multi-sectorial models, for different timelines and geographies, with a greater presence in the literature, or developed by Edward Altman, a unique researcher on this subject, between 1979 and 2014.
Findings: As a main conclusion, in addition to the description of models and techniques, the formulations developed by Carvalho das Neves (1998), Lizarraga (1998) and Monelos et al. (2011) were the best predictors of bankruptcy, up to 6 years before it occurs, for Portuguese and Spanish companies in the transport economic sector (NACE H).
Research, Practical & Social Implications: This information can be used by any interested entity to improve current conditions, optimize and enhance the usage the bankruptcy forecast models.
Originality/Value: The global financial crisis and the growing number of company closures make it crucial to understand the causes of corporate failure, with emphasis on forecasting and anticipating it.
