Abstract:

In this study, the most successful model was performed to determine for modeling and forecasting the volatility of the selected sub-sector return series of each indices which is listed in ISE namely; service (XUHIZ), financial (XUMAL) and industrial (XUSIN) sectors. The findings indicate that the daily data which were analyzed with conditional variance models, covering a period from January 5, 2000 to December 9, 2015, show both ARCH and GARCH effects. In addition, the findings also show that TGARCH (1,1) is the best model for estimating volatility not also financial but also industrial indices, but on the other hand CGARCH (1,1) is the best model to forecast the volatility of service index. Furthermore, EGARCH model which is considering the asymmetry on volatility shocks are also estimated and it was determined that there have a leverage effect on each return series of three indices.

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