Özet:

In this study, it was attempted to determine which model in the volatility modeling of the monthly revenue series of food and beverages (XGIDA), chemistry, oil and plastic (XKMYA), metal, goods and machinery (XMESY), forest, paper and print (XKAGT), stone and soil (XTAST) and textile and leather (XTEKS) sectors covering the dates of 01.1997-07.2019. In the series tested with conditional variable models, volatility has been found to show both the autoregressive conditional variable model (ARCH) and the generalized autoregressive conditional variable model (GARCH) effects. As a result of empirical analyses, in the volatility estimates for food and beverage sectors, the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), the appropriate model is GARCH (1,1), and the appropriate model is GARCH (1,1).

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