Adapting Altman's model to predict the performance of the Palestinian industrial sector

Purpose - This study aims to adopt the Altman model in order to predict the performance of industrial companies listed on the Palestinian Stock Exchange during the period of time between 2013 and 2017. Design/methodology/approach - The study sample consisted of 12 industrial companies listed on the Palestine Stock Exchange, and their financial disclosure period extended for 5 years. Multiple linear regression model was used in the analysis to determine the relationship between the independent variables and the dependent variable where the independent variables were (X1,X2,X3). This study is based on one basic assumption, which is that the Altman's model cannot predict the performance of the Palestinian industrial sector. Findings - The results of the analysis proved the negation of the zero main hypothesis. This means that Altman's model can predict the performance of the Palestinian industrial sector at the level of statistical significance (a = 0.05), as well as the existence of a statistically significant relationship between each of the independent variables (X2,X4,X5) and the dependent variable (Log (Z-score)). Hence, the relationship ofX1andX3with the dependent variable was not statistically significant. Social implications - This paper highlights different challenges that face the adaption of Atman's model and performance prediction in the Palestinian industrial sector. The findings of the analysis have the potential to help future researchers in examining and dealing with new challenges. Originality/value - This paper presents a vital review of adopting Altman's model in the Palestinian industrial sector. A number of recommendations have been made, the most important of which is that most of the companies are located in the red zone. The Altman's model must be adapted in order to fit the Palestinian environment according to the results of statistical analysis and according to a proposed model, which is Log (Z) = −0.653 + 0.72X2 + 0.18X4 + 0.585X5.