Conditional returns distributions generated by a GARCH process, which are important for many problems in market risk … moments of GARCH returns distributions in several ways: we consider a general GARCH model – the GJR specification with a … specific GARCH models largely used in practice are recovered as special cases; we derive the limits of these moments as the …

produced by GARCH-based models are excessive. Therefore we encourage hedgers to use a na ¨ive hedging strategy on the crack … majority of the existing literature, which favours the implementation of GARCH-based hedging strategies. …

Generalized autoregressive conditional heteroskedasticity (GARCH) processes have become very popular as models for … densities and their parametric competitors within different generalized GARCH models such as APARCH and GJR-GARCH. …

GARCH option pricing models have the advantage of a well-established econometric foundation. However, multiple states … need to be introduced as single state GARCH and even Levy processes are unable to explain the term structure of the moments … of financial data. We show that the continuous time version of the Markov switching GARCH(1,1) process is a stochastic …

This article analyzes the issue of American option valuation when the underlying exhibits a GARCH-type volatility …

We use an information-theoretic approach to interpret Engle's (1982) and Bollerslev's (1986) GARCH model as a model for …

generalize the notion of GARCH processes in an information-theoretic sense and are able to capture skewness and kurtosis better …

The Maximum likelihood estimation (MLE) is the most widely used method to estimate the parameters of a GARCH …