Comparison of the combination model with the structural and accounting model in predicting the financial distress

سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 39

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شناسه ملی سند علمی:

JR_IJNAA-15-5_023

تاریخ نمایه سازی: 18 فروردین 1403

چکیده مقاله:

The current research aims to investigate the power of financial distress prediction models while presenting a combination model, comparing the extracted model with the Merton model and the binary logistic regression model in predicting financial distress. In order to achieve the purpose of the research, the information of ۱۶۸ distressed companies selected based on the specific criteria of distress and ۱۶۸ healthy companies admitted to the Tehran Stock Exchange between ۲۰۰۶ and ۲۰۱۹ have been used. After reviewing past studies, ۲۵ variables affecting financial distress, including ۱۷ accounting variables, ۴ market variables, and ۴ macroeconomic variables, were identified, and by emphasizing the frequency and successful performance of these ratios in past studies and performing statistical tests, the final indicators were selected. To determine the dependent variable, Merton's model was used, and finally, by applying the logit model and determining the relationship between the independent variables and the dependent variable, a composite model was extracted. The research results showed that adding economic and stock market variables to financial variables does not increase the ability to predict financial distress and the combined model has better explanatory power than the Merton model and binary logistic regression. In the present research, to predict financial distress, all three categories of accounting, economic and stock market variables are considered together, and the emphasis is not only on accounting variables, and the combined model is compared with the accounting and market model.

نویسندگان

Behnaz Lotfi

Department of Accounting, Faculty of Humanities, Urmia Branch, Islamic Azad University, Urmia, Iran

jamal Bahri Sales

Department of Accounting, Faculty of Humanities, Urmia Branch, Islamic Azad University, Urmia, Iran

Saeid Jabbarzadeh Kangarlouei

Department of Accounting, Faculty of Humanities, Urmia Branch, Islamic Azad University, Urmia, Iran

Mehdi Heydari

Department of Accounting, Faculty of Humanities, Urmia Branch, Islamic Azad University, Urmia, Iran

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