Heteroskedastic Conditional Variance Modeling is a particularly
rich branch of Econometrics. Despite its young age, the literature
embracing variance models is indeed impressive. Statistical
treatment of financial time series has been profoundly enlarged by
this class of models. Many characteristics of financial variables
(leptokurticity, asymmetry,...) can now be modeled. Of course, in
the search for better adjustment, the complexity has been
significantly increased at a non-trivial cost. In this book we
introduce three simple specifications based upon Robinson's (1977)
NLMA model: QMACH, NLMACH and PLMVES. The first proposal belongs to
the NLMA class whilst the second one is closely related to it. Both
possess similar properties as those of the ARCH-class. Our last
proposal, PLMVES, also considers long-memory by means of a new
concept: Pseudo Long-Memory, an artifact allowing for long- memory
modeling. These variance models have advantages none of the
inspiring sources (ARCH and NLMA) possess. This book may help
economists in their quest for a better comprehension of the
variance of economic variables, particularly in the modeling of
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