Comparative Study of Financial Distress Prediction Models: Evidence from Pakistan

• Autor(a) principal: Ashraf, Sumaira
• Data de Publicação: 2017
• Outros Autores: Félix, Elisabete G.S., Serrasqueiro, Zélia
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/22787
• topic: Financial distress; emerging market; prediction models; Z-Score; logit analysis; probit model

Traditional financial distress prediction models performed well for the developed markets, however, their applicability and predictability is limited for the emerging markets especially during the financial crisis. This paper compares the predictability of five most widely used distress prediction models developed by Altman (1968), Ohlson (1980), Zmijewski (1984), Shumway (2001) and Blums (2003) by using up-todate data of emerging market from 2001 to 2015. Furthermore, the study tested the predictive power of the models before, during and after the financial crisis period. Results showed that Probit model has the higher overall prediction accuracy but the Z-Score more accurately predict financially distressed firms of emerging markets. Both models can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets. An important contribution of the paper is the definition of financial distress for the emerging markets where there are no databases with this type of classification. Along with the detailed criteria to classify distressed and non-distressed firms with the large time frame and data set, the study identifies the best predictor of financial distress. This paper also contributes to the literature by checking the changes in the predictability of the models with respect to the financial crisis