Title: Alternative Models for the Conditional Variance
Abstract: Classical GARCH models rely on modelling the conditional variance as a linear function of the squared past innovations. This chapter considers the models that aim at circumventing some of the specified limitations of the standard GARCH models. It focuses on a general class of stochastic recurrence equations (SRE) satisfied by the volatility of most first-order GARCH formulations. The particular SRE can be iterated quite explicitly, and this was used to derive the strictly stationary solution in closed form. The chapter considers volatility models satisfying the SREs. A formulation which seems very close to the exponential GARCH (EGARCH) is the Log-GARCH model. A natural way to introduce asymmetry is to specify the conditional variance as a function of the positive and negative parts of the past innovations. The chapter also focuses on the classical GARCH model and the simplest asymmetric models.
Publication Year: 2019
Publication Date: 2019-03-25
Language: en
Type: other
Indexed In: ['crossref']
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