Considering the challenges related to estimating and forecasting the expected Shortfall dynamically and with a semi-parametric approach, in this study, providing a general framework, dynamic semi-parametric models in forecasting Expected Shortfall in Tehran Stock Exchange be introduced and evaluated. In this regard, the data of the period 2008.12.04-2020.08.26 and Generalized Autoregressive Score (GAS) approach are used to introducing dynamic semi-parametric models (GAS-2F, GAS-1F, GARCH-FZ and hybrid). Then expected Shortfall (ES) in Tehran Stock Exchange be estimated and forecasting performance of these models are compared with traditional models in this field, including GARCH models and rolling window models based on backtesting their results. The results of this study indicate better performance of dynamic semi-parametric models in forecasting the expected Shortfall (ES) than competing models. In addition, the GAS-1F model has shown the best performance among all models.
