Investigating the Correlation of Selected Banks with Dynamic Conditional Correlation (DCC) Model and Identifying Systemically Important Banks with Conditional Value at Risk and Shapley Value Method

Systemic risk arises from simultaneous movement or correlations between market segments; Thus, systemic risk occurs when there is a high correlation between the risks and crises of different market segments or institutions operating in the economy, or when the risks of different segments in a market segment or a country are related to other segments and other countries. This paper presents a measure of systemic risk calculation to effectively describe the systemic importance of each financial institution in a system. The DCC-GARCH methodology with normal and t-student distributions has been used to examine the correlation of time-varying banks. The results of this section show that the application of DCC-GARCH-student-t model is preferable to DCC-GARCH-normal model. In order to investigate the presence of leverage effect, GJR-GARCH model was used and the results of estimation showed the presence of asymmetry and the absence of leverage effect in the data. In the study of dynamic conditional correlation between selected banks, it is also observed that α_C  ,β_C are not significant for both estimation cases. Therefore, in both cases, it is estimated based on the normal distribution and t-student α_C=β_C=0 and the conditional correlation becomes constant. Based on the results of shapley value and in order to allocate the total risk between the banks in the sample, Parsian, Mellat, EN, Tejarat and Saderat banks have the most systemic importance for the period of June 17, 2009 to May 7, 2019.