Bootstrap Prediction Intervals for ARCH Models

In this paper, we construct prediction intervals for autoregressive conditional heteroskedasticity (ARCH) models using the bootstrap. We use both a parametric and non-parametric bootstrap, which take account of parameter uncertainty. We compare our prediction intervals to traditional asymptotic prediction intervals and find that the bootstrap leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the Yen/US$ exchange rate

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Year of publication:	2010
Authors:	Reeves, Jonathan J.
Publisher:	[2010]: [S.l.] : SSRN
Subject:	Bootstrap-Verfahren \| Bootstrap approach \| ARCH-Modell \| ARCH model \| Theorie \| Theory \| Prognoseverfahren \| Forecasting model
Description of contents:	Abstract [papers.ssrn.com]

Extent:	1 Online-Ressource
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: International Journal of Forecasting, Vol. 21, pp. 237-248, 2005 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 7, 2010 erstellt Volltext nicht verfügbar
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013138435