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Estimation in Conditionally Heteroscedastic Time Series Models : LECTURE NOTES IN STATISTICS - Daniel Straumann

Estimation in Conditionally Heteroscedastic Time Series Models


Paperback Published: 19th November 2004
ISBN: 9783540211358
Number Of Pages: 228

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In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic).

This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.

Industry Reviews

From the reviews of the first edition:

"The book deals with conditionally heteroscedastic time series models. It covers classical and new topics of parameter estimation in such models. ... There are a lot of various examples and remarks which clarify the presented general results. Some numerical examples and simulations are given. Detailed discussions and comparisons with known results are presented in each chapter." (Andrew Olenko, Zentralblatt MATH, Vol. 1086, 2006)

Financial time series: facts and models
Some mathematical tools
Parameter estimation: an overview
The QMLE in heteroscedastic time series models: a stochastic recurrence equations approach
Maximum-likelihood estimation in conditionally heteroscedastic time series models
Whittle estimation in a heavy-tailed GARCH (1,1) model
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9783540211358
ISBN-10: 3540211357
Audience: General
Format: Paperback
Language: English
Number Of Pages: 228
Published: 19th November 2004
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 24.77 x 15.88  x 1.91
Weight (kg): 0.38