Volume 9, Issue 32 (7-2018)
jemr 2018, 9(32): 91-128 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rostamzadeh P, Shahnazi R, Neisani M S. Identification of Factors Affecting on Credit Risk in the Iran Banking Industry of Iran Using Stress Test. jemr 2018; 9 (32) :91-128
URL: http://jemr.khu.ac.ir/article-1-1668-en.html
URL: http://jemr.khu.ac.ir/article-1-1668-en.html
1- Shirazu University , parvizrostamzadeh@shirazu.ac.ir
2- Shirazu University
2- Shirazu University
Abstract: (8067 Views)
Credit risk is due to that recipients of the facility, deliberately or involuntarily, don’t have ability to repay their debts to the banking system that this risk is critical in Iran compared to the global. Therefore, the purpose of this study was to investigate the effect of macroeconomic variables on credit risk of Iranian banking industry during the 2006-2016 years and also simulation and prediction of credit risk situation in 2017 under different stress scenarios, bu using stress test. Data used in this research is time series and seasonal. In order to implement a stress test and achieve the purpose of the research, first, the effective macroeconomic variables and the rate of each one's influence on the credit risk are determined using Auto-Regressive Distributed Lags (ARDL). Accordingly, the inflation rate, exchange rate, unemployment rate and housing index in total have a positive effect and variables GDP, the interest rate of bank facilities and the volume of concessional facilities to both government and non-governmental sectors, have a negative impact on credit risk. In the following, using the stress test, simulation of critical situations and prediction of credit risk values in 2017. This was done in three scenarios with titles of mild stress, extreme stress, and hyperstress that in each scenario, different shocks are applied to the variables affecting credit risk. The results of the stress test and scenarios show that the compulsory reduction of interest rates on bank facilities in all three scenarios, initially in the second quarter of 2017, leads to a reduction in credit risk, but rising exchange rates, rising inflation, falling economic growth, as well as accumulation of past values of credit risk, has led to a rapid increase in credit risk and also in scenarios with more severs shocks, has led to catastrophic increase of credit risk in later periods in all scenarios.
Type of Study: Applicable |
Subject:
پولی و مالی
Received: 2018/02/13 | Accepted: 2018/07/18 | Published: 2018/09/12
Received: 2018/02/13 | Accepted: 2018/07/18 | Published: 2018/09/12
References
1. Ahmadian, A. (2014). Analysis of bank stress index in the Iran's banking network. New Economics, 9 (144): 33-35 [in Persian].
2. Allahyari, M. (2014). Using stress test in securitization process. Journal of Investment Knowledge, 4(16): 6-23 [in Persian].
3. Banerjee, A., Dolado, J.J., & Master, R. (1992). On some simple tests for cointegration: The cost of simplicity bank of Spain. Working Paper: 46-53.
4. Bank for international settlements, Basle committee on banking supervision. (1995). an internal model-based approach to market risk capital requirements. Proposal for consultation, Basle, Switzerland.
5. Basel committee on Banking Supervision. (1999). Credit risk modeling: current practices and applications. Basle: Basle Committee Publications.
6. Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system: The case of the GIPS. Economic Modelling, 31: 672-683. [DOI:10.1016/j.econmod.2013.01.027]
7. Castren, O., Dees, S., & Zaher, F. (2010). Stress-testing euro area corporate default probabilities using a global macroeconomic model. Financial Stability, 6 (2): 64-78. [DOI:10.1016/j.jfs.2009.10.001]
8. Corenett, M., Minnick, K., Schorno, J., & Tehranian, H. (2018). An examination of bank behavior around Federal Reserve stress tests. Journal of Financial Intermediation, 35: 1-13. [DOI:10.1016/j.jfi.2018.05.001]
9. Dadbin, M., & Hanjari, S. (2014). A review of crisis tests in the banking industry and suggestions for the banking industry in Iran. The conference of risk management and financial engineering, 2:1-20 [in Persian].
10. Drehmann, M., Sorensen, S., & Stringa, M. (2009). The integrated impact of credit and interest rate risk on banks: A dynamic framework and stress testing application. Journal of Banking & Finance, 33 (4): 713-729. [DOI:10.1016/j.jbankfin.2009.06.009]
11. Enders, J. (2004). Higher Education, Internationalization, and the Nation- State: Recent Developments and Challenges to Governance Theory. Higher Education, 47: 361-382. [DOI:10.1023/B:HIGH.0000016461.98676.30]
12. Eslamloueyan, K., Yazdanpanah, H., & Khalilnezhad, Z. (2018). The existence of a risk-taking channel of monetary policy transmission in Iran's banking system. Journal of Economic Modeling Research, 8 (31): 7-40 [in Persian].
13. Foglia, A. (2009). Stress testing credit risk: a survey of authorities' approaches. Int. J. Central Bank, 5(3): 9-45.
14. Gersl, A., Jakubik, P., Konecny, T., & Seidler J (2012). Dynamic stress testing: the framework for testing banking sector resilience used by the Czech national bank. Czech National Bank, 4-5.
15. Hasan, M.K., Unsal, O., & Tamer, H.E. (2016). Risk management and capital adequacy in Turkish participation and conventional banks: A comparative stress testing analysis. Borsa Istanbul Review, 72-81. [DOI:10.1016/j.bir.2016.04.001]
16. Heidari, H., Zavvarian, Z., & Noorbakhsh, A. (2010). Studying the effect of macroeconomic indices on non-performing loans. Journal of Monetary and Banking Research, 2(4): 191-220 [in Persian].
17. Iran's central bank, Economic indexes and information. Economic reviews and policies organization [in Persian].
18. Iran's statistics center, Statistical data and information, Statistical yearbook, different years [in Persian].
19. Jakubik, P., & Hermanek, J. (2008). Stress testing of the Czech banking sector. Working Paper, 2-13. [DOI:10.18267/j.pep.329]
20. Jakubik, P., & Fungaova, Z. (2012). Bank Stress Tests as an Information Device for Emerging Markets: The Case of Russia. Working Paper, 1-3. [DOI:10.2139/ssrn.2009700]
21. Khodadadi, F., & Mehrara, M. (2017). Effect of macroeconomic fluctuations on the lending behavior of commercial banks in Iran. Journal of Islamic Economics & Banking, 15 (18): 23-39 [in Persian].
22. Mashayekh, S., Moghaddasi, M. (2017). Stress testing: A new approach for risk management with emphasis on banks' capital requirement, Journal of Accounting Research, 1: 35-52 [in Persian].
23. Mitrovic, M., Busch, R., & Koziol, P. (2017). Many a little makes a mickle: Stress testing small and medium-sized German banks. The Quarterly Review of Economics and Finance, 253-237. [DOI:10.1016/j.qref.2017.08.001]
24. Nili, F., Heidari, H., & Saberian Ranjbar, S. (2012). The impact of macroeconomic variables on banks' balance sheet: a stress test approach. Journal of Monetary and Banking Research, 8: 43-86 [in Persian].
25. Pesaran, M.H., & Smith. R.J. (1998). Structural analysis of Co-integration VARs. Journal of Economic Surveys, 471-505. [DOI:10.1111/1467-6419.00065]
26. Rodriguez, A., & Trucharte, C. (2007). Loss coverage and stress testing mortgage portfolios: a non-parametric approach. J. Financ. Stabil, 3 (4): 342-367. [DOI:10.1016/j.jfs.2007.09.002]
27. Saberian Ranjbar, S., Heidari, H. (2010). Introducing of tests to assess the vulnerability of a financial system. New Economics, 8(130), 147-152 [in Persian].
28. Salehabadi, A., Allahyari, M. (2016). The use of stress testing in regulatory and supervisory perspectives. Journal of Investment Knowledge, 5(19): 213-233 [in Persian].
29. Savas, O. Bulent, D., & Alper, A. H. (2016). Macro stress testing and an application on Turkish banking sector. Istanbul Conference of Economics and Finance: 25-48.
30. Sedghi, H. (2013). Credit risk simulation in critical situations for the banking system of selected countries. 1st National Conference of Monetary and Banking Management Development, 1: 1-20 [in Persian].
31. Shavvalpour, S., Ashari, E. (2013). Determining the relationship between credit risk & profitability in Iranian banks. Journal of Financial Reasearch, 2: 234-236 [in Persian].
32. Soori, A., Tashkini, A., & Saadat, M. R. (2010). The effect of concentration, merger, and e-banking activity on efficiency of Iranian money marketing. Journal of Economic Modeling Research, 1(2): 115-144 [in Persian].
33. Vazquez, F., Tabak, B. M., & Souto, M. (2012). A macro stress test model of credit risk for the Brazilian banking sector. Working Paper, 3-50. [DOI:10.1016/j.jfs.2011.05.002]
34. Yurdakul, F. (2014). Macroeconomic Modelling Of Credit Risk for Banks. Social and Behavioral Sciences, 109: 784-793. [DOI:10.1016/j.sbspro.2013.12.544]
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
