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Titlebook: Bootstrapping Stationary ARMA-GARCH Models; Kenichi Shimizu Book 2010 Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH, Wiesbade

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发表于 2025-3-21 17:57:30 | 显示全部楼层 |阅读模式
期刊全称Bootstrapping Stationary ARMA-GARCH Models
影响因子2023Kenichi Shimizu
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图书封面Titlebook: Bootstrapping Stationary ARMA-GARCH Models;  Kenichi Shimizu Book 2010 Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH, Wiesbade
影响因子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..
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发表于 2025-3-21 20:15:45 | 显示全部楼层
Parametric AR(p)-ARCH(q) Models,eters by the ordinary least squares (OLS) method and adopt the two-step estimation for the ARCH part, in which the parameters of the ARCH part are estimated based on the residuals of the AR part. In the first section we sketch the estimation theory for the parametric AR (.)-ARCH (.) model with the O
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Semiparametric AR(p)-ARCH(1) Models, nonparametric. In the first section we introduce the semiparametric AR (.)-ARCH (1) model and show the asymptotic properties of the estimators. Then, as in preceding chapters, possible applications of the residual and the wild bootstrap are proposed and their weak consistency proved. The theoretica
发表于 2025-3-22 10:40:51 | 显示全部楼层
Range-Free Network Localization, methods. In empirical studies, however, the limit of bootstrap tends to be underestimated, and the technique is sometimes regarded as a utility tool applicable to all models. Let us see a typical misunderstanding of bootstrap in econometric literature.
发表于 2025-3-22 15:50:07 | 显示全部楼层
Location, Localization, and Localizabilityeters by the ordinary least squares (OLS) method and adopt the two-step estimation for the ARCH part, in which the parameters of the ARCH part are estimated based on the residuals of the AR part. In the first section we sketch the estimation theory for the parametric AR (.)-ARCH (.) model with the O
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Parametric ARMA(p, q)- GARCH(r, s) Models,st section we sketch the estimation theory based on Francq and Zakoïan (2004). Then, analogously to the previous chapter, possible applications of the residual and the wild bootstrap are proposed and their weak consistency investigated. These theoretical results are confirmed by simulations in the last section
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