Evaluating financial distress in Portuguese firms

: revisiting Altman's Z-score model

Abstract

This thesis significantly advances the field of financial distress prediction in Portuguese companies by meticulously refining Altman's seminal Z-Score model (1983). With strategic updates to the model's parameters using the latest financial data, this research not only improves predictive accuracy but fundamentally transforms the tool to meet the contemporary needs of Portugal's dynamic economy. By transitioning from multiple discriminant analysis to logistic regression, the study introduces a robust methodological enhancement that substantially increases the model’s predictive precision. Furthermore, the integration of macroeconomic indicators such as GDP has revolutionized its predictive capabilities, proving indispensable in today's interconnected financial landscape. However, the research also unveils limitations; elements such as year dummies, company size, age, and sector-specific factors did not markedly influence the model’s effectiveness, prompting a revaluation of traditional assumptions in distress prediction. This thorough analysis of diverse firm characteristics emphasizes the critical need for financial models that are specifically adapted to the distinct economic features of the Portuguese market. These insights offer invaluable guidance for financial institutions, investors, and policymakers, significantly enhancing the utility and application of distress prediction models across diverse economic environments. Ultimately, the refined model does not just promise better risk management—it guarantees more informed, strategic decision-making for stakeholders within the SME-dominated Portuguese market.

Date of Award	15 Oct 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Ricardo Reis (Supervisor)