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Bootstrapping Stationary ARMA-GARCH Models
Buch
Buch
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Fachbuch
2010

Bootstrapping Stationary ARMA-GARCH Models

ISBN
EAN
978-3-8348-0992-6
9783834809926
Artikel-Nr.
76Z4DQG
Sofort lieferbar:
2
Kostenloser Versand
Rabatt
-13.1
%
CHF 111.00
CHF
96.48
Anzahl
1
Maximale
Lieferzeit
5
Arbeitstage
Donnerstag
30.09.2021
speech-bubble-svg Beschreibung
Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it is widely applied for risk management. Bootstrap is without doubt a promising technique, however, it is not applicable to all time series models. A wrong application could lead to a false decision to take too much risk.

Kenichi Shimizu investigates the limit of the two standard bootstrap techniques, the residual and the wild bootstrap, when these are applied to the conditionally heteroscedastic models, such as the ARCH and GARCH models. The author shows that the wild bootstrap usually does not work well when one estimates conditional heteroscedasticity of Engle’s ARCH or Bollerslev’s GARCH models while the residual bootstrap works without problems. Simulation studies from the application of the proposed bootstrap methods are demonstrated together with the theoretical investigation.
Inhaltsverzeichnis
Bootstrap does not always work - parametric AR(p)-ARCH(q) models - parametric ARMA(p,q)-GARCH(r,s) models - semiparametric AR(p)-ARCH(1) models
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Herausgeber/-in
Autorenporträt
Dr. Kenichi Shimizu completed his doctoral thesis at the Department of Mathematics at the Technical University, Braunschweig.
Zielgruppe
Research
Publikation
Deutschland
27.01.2010
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Sprachen
Englisch
Deutsch
book-svg Format
Softcover
148 Seiten
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Kostenloser Versand: Schweiz & Liechtenstein
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