Using Altman Z”- Score to Predict Financial Distress: Evidence from Lebanese Alpha Banks

Document Type : Research Paper


1 Department of Banking, Belarus State Economic University (BSEU), Minsk, Belarus

2 Department of Finance, Cyprus International University (CIU), Nicosia, North Cyprus

3 Faculty of Economics and Business Administration, Branch 6, Lebanese University (LU), Rashaya, Lebanon

4 Faculty of Economics and Business Administration, Lebanese University (LU), Beirut, Lebanon


The main purpose of this research is to prove the validity of the Altman Z”-score model to expect the financial distress in the Lebanese Alpha banks over the period 2009 - 2018. The study begins with a literature review of secondary data from articles, books, financial reports, previous researches, and periodicals on the Lebanese Alpha Banks. The researchers calculated the Altman Z”-score for non-manufacturing companies and emerging markets. Moreover, to reach the specific goal of this study, the researchers used EViews Software and applied (1) a descriptive analysis of the variables (X1, X2, X3, X4, and Z”) and (2) the Pearson Correlation Matrix to study the impact of the independent variables on the dependent variable. The authors validated the Altman Z”-score Model using the four independent variables. In addition to that, the correlation of the variables indicated that there is a strong positive correlation between X1 and Z” and a weak negative correlation between X2 and Z” and a weak positive correlation between X3 and X4 and Z”. Above all, based on the calculated values for the Z” for non-manufacturing companies and emerging markets, the majority of the ten Alpha Banks had values below the cutoff of 1.1 which showed evidence that they were distressed over the period 2009 - 2018. It is worth it noting, based on the results, that the Z”-score model is recommended as an important, instrumental indicator for any external or internal use of banks’ financial statements like auditors, financial managers, investors, and lenders, to take the correct decisions in case of financial distress or failure of these institutions.