Z-Score and Z’-Score

44 private-sector companies in Serbia (Belgrade Stock Exchange)


There is no significant difference between the Z-Score calculation methods. The results were not very expressive, whose explanation is directly linked to the local characteristics, different sectors, and the limited period

Size of the sample available for the capital market of Serbia. The financial indicators of taxes on profit were not published for some companies, which reduces the power of analysis. Moreover, the capital market in Serbia does not reflect the real value of the shares (it is an incipient market that is of little relevance in the country’s economy)


Z-Score and Z’-Score

477 companies located in Malaysia (eight industries)

May 31, 2010

The results of the calculated models are significantly different, with a smaller number of companies in the gray zone

A single period of data collection limits the analysis, mainly due to the perception of investors about a more liberal policy in the study period



40 Greek companies listed on the Hellenic Stock Market (Athexgroup)


The model identified 86% of the group of bankrupt companies, but did not show good performance for companies that did not go bankrupt (18% of prediction appropriate)

The period of economic instability in Greece (persistent recession) affects the data of companies with better financial conditions and the most vulnerable ones (corporate indebtedness becomes much larger). Additionally, the proportion of firms in each segment is not equal



11 manufacturing companies in Lebanon (4 small/medium and 7 large)


Z’-Score proved to be accurate, including for the classification of companies regarding size

Sample size, sample period are constraints in the analysis. Furthermore, Lebanese companies do not follow the same accounting regulations as US companies


Z-Score and Z’-Score

44 private-sector companies in Serbia (Belgrade Stock Exchange)


Original Z-Score model showed weak understanding, but the Z’-Score indicated more relevant results

Specifics of the local economy may reflect results, such as: low competitiveness of companies vis-à-vis other countries, chronic lack of liquidity in the economy, and exchange rate risk



399 individual farmers in Illinois (USA)


The model presented inconsistencies due to differences in relations between financial companies and borrowers (different capacity among farmers)

Specificity of the target market of the study, which suggests a possible model with discriminant function for agricultural purposes