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Erschienen in:
Definition of Long Memory Kapitel lesen Erstes Kapitel lesen

2013 | OriginalPaper | Buchkapitel

6. Statistical Inference for Nonlinear Processes

verfasst von : Jan Beran, Yuanhua Feng, Sucharita Ghosh, Rafal Kulik

Erschienen in: Long-Memory Processes

Verlag: Springer Berlin Heidelberg

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Abstract

In this section, we consider nonlinear processes with long memory. We will mainly focus on volatility models: stochastic volatility (see Definitions 2.3–2.4 and Sect. 4.​2.​6 for limit theorems), ARCH(∞) processes (see Definition 2.1 and Sect. 4.​2.​7) and LARCH(∞) models (see (2.​47) and (2.​48), and Sect. 4.​2.​8). Statistical inference for traffic models is not well developed yet (see Faÿ et al. in Queueing Syst. 54(2):121–140, 2006, Bernoulli 13(2):473–491, 2007; Hsieh et al. in J. Econom. 141(2):913–949, 2007 for some results in this direction).

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Vorheriges Kapitel Statistical Inference for Stationary Processes
Nächstes Kapitel Statistical Inference for Nonstationary Processes
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Metadaten
Titel
Statistical Inference for Nonlinear Processes
verfasst von
Jan Beran
Yuanhua Feng
Sucharita Ghosh
Rafal Kulik
Copyright-Jahr
2013
Verlag
Springer Berlin Heidelberg
Buch
Long-Memory Processes

Print ISBN: 978-3-642-35511-0

Electronic ISBN: 978-3-642-35512-7

Copyright-Jahr: 2013

DOI
https://doi.org/10.1007/978-3-642-35512-7_6