The dynamics of the beta coefficient of stock prediction in the framework of structural macroeconomic models

The present research is aimed at predicting the beta coefficient (systematic risk) prediction dynamics within the framework of two macroeconomic structural models, the model in the context of dynamic stochastic general equilibrium (DSGE) and Panel Vector Autoregressive (PVAR) with the inclusion of financial data of companies and Some of the facts observed in the Iranian economy during the 15-year period (2002-2016). The results of the research show that economic shocks affect the beta coefficient of the stock. Also, in three approaches to predict stock beta coefficient, the VAR model has a lower error than the DSGE model. Finally, by comparing the moments of the present variables in the DSGE model and the real data of Iran's real moments, it shows the relative success of this model in the realities of Iran's economy.