ALL IN THE FAMILY - NESTING SYMMETRICAL AND ASYMMETRIC GARCH MODELS

This paper develops a parametric family of models of generalized autor egressive heteroskedasticity (GARCH). The family nests the most popula r symmetric and asymmetric GARCH models, thereby highlighting the rela tion between the models and their treatment of asymmetry. Furthermore, the structure permits nested tests of different types of asymmetry an d functional forms. Daily U.S. stock return data reject all standard G ARCH models in favor of a model in which, roughly speaking, the condit ional standard deviation depends on the shifted absolute value of the shocks raised to the power three halves and past standard deviations.