文章基本信息
- 标题：Bayesian Estimation of Change-Point in Unobserved-ARCH Models
- 本地全文：下载
- 作者：Fazlollah Lak
- 期刊名称：World Applied Sciences Journal
- 印刷版ISSN：1818-4952
- 电子版ISSN：1991-6426
- 出版年度：2008
- 卷号：3
- 期号：03
- 出版社：International Digital Organization for Scientific Information Publications
- 摘要：
Change-point problem deals with sudden change in the distribution of a set of given data.
Change in financial time series is a common event, because many factors for example some news, etc. may
affect the series and cause change. In this work, we intend to detect the time of change-point, using
Bayesian methods in Unobserved-ARCH models. We estimate the model and the time of the change-point.X - 关键词：Bayesian change-point · Gibbs and Metropolis -Hastings algorithms · Monte Carlo Markovchain · Unobserved-ARCH Modelsin
