A Model for Predicting Corporate Default in Tehran Stock Exchange
| Autor: | Ghasem Bolo (Ph.D), Maysam Ahmadvand |
|---|---|
| Jazyk: | perština |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | مجله دانش حسابداری, Vol 10, Iss 1, Pp 1-38 (2019) |
| Druh dokumentu: | article |
| ISSN: | 2008-8914 2476-292X |
| DOI: | 10.22103/jak.2019.12359.2730 |
| Popis: | Objective: The corporate default is one of the most abrasive events in the life of a corporation. Costs and risks inherent in this event have caused various models be advised and introduced within the past four decades to measure and predict the corporate default. Considering the importance of the subject, this study aims to introduce an appropriate model for predicting the corporate default in the selected industries in the Tehran Stock Exchange, TSE, using a sample of 100 firms. Method: In this study, first, the factors affecting the corporate default were identified by conducting library research and applying the fuzzy Delphi method. Second, the drivers of corporate default were introduced, and then, a default predicting model in the TSE framework was introduced, using partial least squares structural equation modeling (PLS-SEM). Results: The findings showed that the following ratios could be considered successfully the drivers of corporate default in the TSE: net income to total assets,earnings before interest and tax to total assets, retained earnings to total assets, current assets to current liabilities, net working capital to total assets, cashto current liabilities, current liabilities to total assets, total liabilities to total assets, cash flow from operating activities to sales, and cash flow from operating activities to total liabilities. Conclusion: It is found that in the TSE only the accounting ratios could be accepted as the corporate default drivers. The other potential drivers such as market variables, macroeconomic indicators, non-financial factors, and earnings quality measures do not play any role in corporate default predicting in the TSE. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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