Modeling Volatility: Evidence from Tehran Stock Exchange



The research problem investigated in this paper is modeling volatility and analyzing risk and return’s relationship in Tehran Stock Exchange using GARCH-family models including GARCH(1,1), GARCH(2,2), EGARCH(1,1), PGARCH(1,1), TGARCH(1,1), GARCH(1,1)-M and CGARCH(1,1). Using the daily returns of Tehran Stock Exchange companies, we focused on two portfolios of all the companies during a 10-year-period and those liquid ones during a 5-year-period. In order to meet the distributional characteristics of the financial time series, we have used Normal, t-Student and GED distributional assumptions. The results of this survey and applied research show that first, the conditional volatility models best succeed in modeling characteristics of financial data including volatility clustering, long memory and leverage effects. Second, for both portfolios, increased risk will lead to a rise in the returns.