Nowadays operational research has become a part of financial re-search. One way that operational research can be used in financial re-search is designing financial distress prediction models. In this re-search we designed a financial distress prediction model based on lo-gistic regression and on financial ratios and efficiency scores. For this purpose, we designed and tested two models: 1- financial distress pre-diction model based on logistic regression that was designed by finan-cial ratio variable 2- financial distress prediction model based on lo-gistic regression that was designed by financial ratio and efficiency score variables. Efficiency score variable was calculated by Data En-velopment Analysis (DEA). The results show that these models are able to predict the financial distress of production corporations in Te-hran stock exchange two years prior to its occurrence. The results of the two models and comparison of them show that although efficiency score variable can improve the results of financial distress prediction models but the differences between the accuracy of predictions of fi-nancial distress in two models are not significant.
Mousavi Shiri, S., & Tabarestani, M. (2020). The Ability of a Model Based on Logistic Regression in Prediction of Financial Distress and Effectiveness of Efficiency Score in Improving the Model. Commercial Strategies, 9(47), 429-444.
MLA
S.M Mousavi Shiri; M.R Tabarestani. "The Ability of a Model Based on Logistic Regression in Prediction of Financial Distress and Effectiveness of Efficiency Score in Improving the Model". Commercial Strategies, 9, 47, 2020, 429-444.
HARVARD
Mousavi Shiri, S., Tabarestani, M. (2020). 'The Ability of a Model Based on Logistic Regression in Prediction of Financial Distress and Effectiveness of Efficiency Score in Improving the Model', Commercial Strategies, 9(47), pp. 429-444.
VANCOUVER
Mousavi Shiri, S., Tabarestani, M. The Ability of a Model Based on Logistic Regression in Prediction of Financial Distress and Effectiveness of Efficiency Score in Improving the Model. Commercial Strategies, 2020; 9(47): 429-444.
