مقایسه معیارهای تشخیص شرکت‌های درمانده مالی با استفاده از رگرسیون لجستیک و روش‌های هوش مصنوعی

نوع مقاله : علمی - پژوهشی

نویسندگان

1 کارشناسی ارشد حسابداری، دانشگاه ارومیه، ارومیه ایران.

2 دانشیار گروه حسابداری، دانشگاه ارومیه، ارومیه، ایران.

3 استادیار گروه حسابداری، دانشگاه ارومیه، ارومیه، ایران.

چکیده

در محیط رقابتی امروز و با تغییرات شرایط بازارها، احتمال درماندگی مالی شرکت‌ها افزایش یافته است. در این شرایط افراد، شرکت‌های سرمایه‌گذار و سازمان‌های مالی تلاش زیادی برای اطلاع از وضعیت فعلی و آتی شرکت‌های سرمایه‌پذیر در جهت محافظت از سرمایه خود انجام می‌دهند. ارزیابی و تشخیص صحیح وضعیت مالی شرکت‌ها و همچنین پیش‌بینی وضعیت مالی آتی آن‌ها نیازمند استفاده از معیارهای کارآمد با احتمال خطای کمتر است؛ بنابراین هدف این پژوهش رتبه‌بندی معیارهای منتخب در شناسایی بهتر شرکت‌های درمانده مالی است. بدین منظور پس از بررسی و شناسایی پرکاربردترین معیارها و مدل‌های تشخیص شرکت‌های درمانده، با استفاده از آن‌ها شرکت‌های درمانده «بورس اوراق بهادار تهران» طی سال‌های 1384 تا 1396 از شرکت‌های غیردرمانده (سالم) تفکیک و با استفاده از نتایج حاصل از رگرسیون لجستیک و روش‌های هوش مصنوعی و معیارهای ماده 141 قانون تجارت ایران، آلتمن (1968)، آلتمن (1995) و آسکویت و همکاران (1994) مقایسه شدند. نتایج نشان داد در دوره مورد ­بررسی و در شرایط حاکم بر شرکت‌های ایرانی مستقر در «بورس اوراق بهادار تهران»، معیار آسکویت و همکاران (1994)، بهترین روش برای شناسایی شرکت‌های درمانده مالی است و معیارهای آلتمن (1995)، ماده 141 قانون تجارت ایران و آلتمن (1968) در اولویت‌های بعدی از لحاظ شناسایی شرکت‌های درمانده قرار گرفتند.

کلیدواژه‌ها

عنوان مقاله [English]

Comparing the Identifying Criteria for Financially Distressed Companies using Logistic Regression and Artificial Intelligence Methods

نویسندگان [English]

  • Alireza Aliakbarlou 1
  • Gholamreza Mansourfar 2
  • Farzad Ghayour 3
1 MSc of Accounting, Urmia University, Urmia, Iran.
2 Associate Prof, Department of Accounting, Urmia University, Urmia, Iran
3 Assistant Prof, Department of Accounting, Urmia University, Urmia, Iran.
چکیده [English]

In current competitive environment, the risk of financial distress of companies has increased, in this situation, individuals and corporations and financial institutions make a lot of effort to learn about the status of Investee companies to protect their capital. The assessment and recognition of the firm's financial condition requires utilizing efficient measures with less error probability, Therefore, the purpose of this study is to compare the different criteria for identifying financially distressed companies. For this purpose, after reviewing and identifying the most important criteria and models for identifying distressed companies from non-distressed corporations, the distressed companies of Tehran Stock Exchange during the years 2006 to 2018 were separated from healthy firms and compared with the results of logistic regression and artificial intelligence methods, Article 141 of the trade law, Altman (1968), Altman (1995) and Asquith et al (1994). The results of this study showed that during the period under review and in the conditions of the Iranian companies based on Tehran Stock Exchange that Asquith et al (1994) criteria is the best way to identify distressed companies and to predict the financial position of companies and the Altman criteria (1995), Article 141 of the trade law and Altman (1968) are among the top priorities in identifying distressed enterprises.

کلیدواژه‌ها [English]

  • Distress Distinction Criteria’s
  • Logistic Regression
  • Artificial Intelligence Methods

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چشم انداز مدیریت مالی
دوره 10، شماره 29 - شماره پیاپی 29
اردیبهشت 1399
صفحه 147-166

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