Investigating the Application of Extreme Value Theory in Estimating Liquidity Risk of Accepted Banks in Tehran Stock Exchange

Measuring and estimating the risk is a problem that has long been of concern to the researchers. Various approaches have been proposed in this regard. These approaches can be categorized based on statistical techniques used in three categories: parametric, semi-parametric, and nonparametric approaches, so that risk-based measures often measure and estimate risk. Among the various risk measures, the extreme value is emerging gauges. The purpose of this study is to compare the etreme method with the conventional method in 10 banks accepted in Tehran Stock Exchange which has been investigated in the period of seven years from 2011-2017. To do this, Garch and EGarch have been used to estimate the risk. The results of the study showed that the accuracy of risk estimation with extreme value method and GARCH estimation was higher than conventional risk method. While the accuracy of risk estimation with a extreme method and an estimation of the EGarch is less than that of conventional.