Abstract:

Using nonlinear conditional Heteroscedasticity model has become widespread because of their characteristic in financial time series. This study deals with univariate ARCH-GARCH models theoretically and practically. During application heteroscedasticity models in stock exchange market were examined and the determination of the appropriate models for IMKB series was aimed. Autoregressive Conditional Heteroscedasticity (ARCH), Generalized ARCH (GARCH), Exponential GARCH (EGARCH), ARCH in Mean (ARCH-M), GARCH in Mean (GARCH-M) and Threshold ARCH (TARCH) were studied. In the last part, an application of ARCH models IMKB100 index, financial index and industrial index that calculated at IMKB data were modeled and done.