Evaluation of the Effect of Contagion Risk on the Macroeconomic Performance of Iran and Identifying Too-Connected-To-Fail (TCTF) Banks

Seraj, Mostafa; Tehrani, Reza; Fallahpour, Saeed

doi:10.22096/esp.2020.113967.1267

Evaluation of the Effect of Contagion Risk on the Macroeconomic Performance of Iran and Identifying Too-Connected-To-Fail (TCTF) Banks

Document Type : Original Article

Authors

Mostafa Seraj ¹

Reza Tehrani ²

Saeed Fallahpour ³

¹ Ph.D. Student in Finance, Faculty of Management, University of Tehran, Iran.

² Prof., Faculty of Management, University of Tehran, Tehran, Iran.

³ Assistant Prof., Faculty of Management, University of Tehran, Tehran, Iran.

10.22096/esp.2020.113967.1267

Abstract

The interbank market and the activity of banks in financial markets have led to the interconnectedness of banking system. In the normal situation, the interconnectedness will make the system more stable, but in a turbulent condition, the crisis will quickly spread to the entire banking network. In order to effective policy making in financial stability, continuous measurement and monitoring of the level of contagion in the banking network and studying the mechanism of its impact on macroeconomics is required. This paper evaluates the risk of contagion by using Dynamic causality statistics (DCI), and has identified the banks that have a systemic importance in terms of contagion or so-called too-connected-to-fail (TCTF). The relationship between GDP changes and the value added of the financial sector with changes in the DCI index of Iran's banking sector has been evaluated using Granger causality, which indicates a negative relationship up to 12-month time horizon. In order to take a timely measure for decreasing the adverse effects of systemic risks, Policy-makers should monitor DCI index continuously.

Keywords

Contagion

Dynamic Causality Index (DCI)

Granger Causality

Too-connected-to-Fail (TCTF) banks

BabaJani, J.; Taghavi Fard, M. & Ghazali, A. (2018). "A framework for measuring and predicting system risk with the conditional value at risk approach", Financial Knowledge of Securities Analysis, Vol: 11, No.39, pp. 15-36.
Botshekan, M.H. & Mohseni, H. (2017). "Volatility Spillover and Dynamic conditional correlation of exchange rate on banks stock index", Journal of Monetary and Banking Research, Vol. 10, No.31, pp. 1-28.
Danesh Jafari, D.; Mohammadi, T.; Botshekan, M.H. & Pashazadeh, H. (2017). "Analysis of the Systemic Risk in the Banking System Using Dynamic Conditional Correlation (dcc)", Journal of Monetary and Banking Research, 10, No. 33, pp. 457-480.
Eivazloo, R. & Rameshg, M. (2019). "Measuring systemic risk in the financial institution via dynamic conditional correlation and delta conditional value at risk mode and bank rating", Journal of Asset Management and Financing, Vol. 7, No. 4, pp. 1-16.
Farzinvash, A.; Elahi, N.; Gilanipour, J. & Mahdavi, G. (2017). "The evaluation of Systemic Risk in the Iran Banking System by Delta Conditional Value at Risk (CoVaR) Criterion",Financial Engineering and Portfolio Management, Vol. 8, No. 33, pp. 265-281.
Rahimi Baghi, A.; ArabSalehi, M. & Vaez Barzani, M. (2019). "Assessing the Systemic Risk in the Financial System of Iran using Granger Causality Network Method". Financial Research Journal, Vol. 21. No. 1, pp. 121-142.