عنوان مقاله [English]
The purpose of this paper was to investigate the effect of macroeconomic and specific banking variables on systemic risk using the Coppola function approach and conditional risk value. In this study, the statistical information of banks during the years 2014-2019 was used. For this purpose, by calculating the marginal distribution, we calculate the Capula function and to interpret the dependence between two time series of the Gumble-Gapchal DCC function. The results indicated that banks' returns were more dependent on the upper distribution trail. Accordingly, these indices are more dependent on negative returns than positive returns. According to the estimated model, the conditional risk value was calculated for the studied banks. The results showed that the systemic risk of different banks was significantly different. Finally, the impact of macroeconomic and financial variables on systemic risk was estimated. The results indicated that the high risk value among banks had a direct effect on CoVaR index. To measure the effect of bank size on systemic risk index, two variables of company size and cash flow were included as explanatory variables in the model. . According to the results of the estimation, the size of the company and the banks' cash flow had a negative effect on the CoVaR index, while the banks' ROA had a positive and significant effect on the banks' systemic risk.