The contagiousness of the risk of financial distress in Iranian banks with a dynamic conditional turbulence approach

Document Type : Original Article

Authors
Behrouz Barzegar 1
mir feiz Fallah Shams 2
maryam khalili araghi 3
hashem nikoomaram 4
1 PhD Student in Financial Management, Department of Financial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 Associate Professor, Department of Financial Management, Faculty of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
3 Assistant Professor, Department of Business Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
4 Professor, Department of Accounting, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran .
Abstract
In the present study, the effect of the spread of financial distress in Iranian banks with a dynamic conditional turbulence approach for the use of economic decision makers and financial managers has been investigated.
The statistical population of the study includes Mellat, Tejarat, Saderat and Parsian banks, which have been analyzed in the period of 2016-2016. The present study, using the KMV method and the concept of distance to default, and using the VAR model and the DCC-GARCH method, has investigated the possibility of spreading financial distress to other banks.
The results show that there is a significant relationship between the risk of financial helplessness of banks with each other; Bank Mellat has the highest risk of transmission of helplessness and Parsian Bank shows the least effectiveness. According to the results of the model, increasing the operational risks of banks, including credit risk and market risk, has a significant effect on increasing the risk of financial distress and this risk can spread to other banks in the banks' communication network and then the entire economy.
Keywords
financial helplessness
helplessness risk spread
credit risk
banking network
market risk
  • ابوالحسنی ، محمد جواد و صمدی ، سعید ( 1399 ) ، ارزیابی مدلهای پانل پروبیت ساده و پویا در پیش بینی بحرانهای بانکی ، فصلنامه پژوهش های پولی-بانکی ، سال سیزدهم ،شماره ۴۵ ،صص 393- 434
  • بولو ، قاسم ؛ اعرابی ، مهران ( 1398 ) ، شناسایی عوامل مؤثر بر ریسک جامع بانک های دولتی ، دو فصلنامه علمی حسابداری دولتی ، سال پنجم شماره 2( پیاپی 10) ، صص 46-25
  • شجاع وشوشاد ، محسن ؛ زمردیان ، غلامرضا ؛ پورزرندی ، محمدابراهیم ؛ مینویی ، مهرزاد ، ( ۱۴۰۰) ، بررسی سرایت پذیری ریسک درماندگی مالی و ریسک اعتباری در نظام بانکی کشور ، فصلنامـه علمی پژوهشی دانش سرمایه گـذاری ، صص ۳۱۳-۳۳۹
  • دلنواز ، بیتا ، ( 1398) ، بررسی ریسک فراگیر درماندگی مالی بین شرکت های زنجیره تامین خودرو در بورس اوراق بهادار تهران ، فلاح شمس ، میرفیض ، دانشکده مدیریت و اقتصاد، دانشگاه آزاد اسلامی واحد تهران مرکزی
  • زرین ، جعفر ؛ جمشیدی نوید ، بابک ؛ قنبری ، مهرداد و باغ فلکی ، افشین ( 1399 ) عنوان تدوین الگوی پیش بینی ورشکستگی شرکت های دولتی با استفاده از متغیرهای کلان اقتصادی، مدیریتی ، مالی و سیاسی،دوفصلنامه علمی حسابداری دولتی ، سال هفتم ،شماره ( 1) ، 96-79
  • Bhattacharya, M. Nkwoma , John &Rebecca Valenzuela, M. (2020). Credit risk and financial integration: An application of network analysis. International Review of Financial Analysis 72,101588  

*       Jowita, G (2020) Determinants of the bankruptcy risk of commercial banks in Central and Eastern Europe Prace Naukowe University to Economic znigo we  Wroclawiureserch Papers of wroclaw university of economics and business  2020, vol. 64, nr 1   ISSN1899-3192 e-ISSN 2392-0041  55-65

  • Hafeez, U . Zhuquan ,W . Muhammad , G , A ., Fan ,  Umeair , S. Memon Rafait  ,   M ( 2021 ) , Association of Financial Distress and Predicted Bankruptcy: The Case of Pakistani Banking Sector , Journal of Asian Finance, Economics and Business Vol 8 No 1 (2021) 573–585
  • Wang, X. W., Cao, Y. M., & Park, C. (2019). The relationships among community experience, community commitment, brand attitude, and purchase intention in social media. International Journal of Information Management, 49, 475-488
  • Diks, C., Hommes, C., & Wang, J. (2019). “Critical slowing down as an early
    warning signal for financial crises?” Empirical Economics, 57(4), 1201-1228.
  • Jan, A., Marimuthu, M., Shad, M. K., Zahid, M., & Jan, A. A. (2019). “Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis.” Economic Change and Restructuring, 52(1), 67-87.
  • Mahfuzur Rahman , Cheong Li Sa  and Md. Abdul Kaium Masud (2021) Predicting Firms’ Financial Distress: An Empirical Analysis Using the F-Score Model , Journal of Risk and Financial
    Management 14: 199. https:// doi.org/10.3390/jrfm14050199 : pp 1-16
  • Caprio, G., & Klingebiel, D. (1996, April). Bank insolvency: bad luck, bad policy, or bad banking?. In Annual World Bank conference ondevelopment economics (Vol. 79).
  • Davis, E. P., & Karim, D. (2008). “Comparing early warning systems for banking crises.” Journal of Financial stability, 4(2), 89-120.