Könyv Bootstrapping Stationary ARMA-GARCH Models Kenichi Shimizu

Bootstrapping Stationary ARMA-GARCH Models

Szerző: Kenichi Shimizu
Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
19 223 Ft
Bootstrap technique is a useful tool for assessing uncertainty in statistical estimation and thus it...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
148
EAN
9783834809926
ISBN
9783834809926
Enbook ID
08923897
Súly
295
Méretek
148 x 210 x 8

Teljes leírás

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 the 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. Together with the theoretical investigation simulation studies from the application of the proposed bootstrap methods are demonstrated.

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