Quasi-maximum likelihood estimation for multiple volatility shifts

被引：0

作者：

Kim, Moosup ^{[1
]}

Lee, Taewook ^{[2
]}

Noh, Jungsik ^{[1
]}

Baek, Changryong ^{[3
]}

机构：

[1] Seoul Natl Univ, Dept Stat, Gwanak Ro 151742, Gwanak Gu, South Korea

[2] Hankuk Univ Foreign Studies, Dept Stat, Yongin 449791, Kyunggi Do, South Korea

[3] Sungkyunkwan Univ, Dept Stat, Seoul 110745, South Korea

来源：

STATISTICS & PROBABILITY LETTERS | 2014年 / 86卷

基金：

新加坡国家研究基金会;

关键词：

Volatility shifts; Change point analysis; Quasi-maximum likelihood estimation; TIME-SERIES; MODELS; NUMBER; BREAKS;

D O I：

10.1016/j.spl.2013.12.007

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose the Gaussian quasi-maximum likelihood estimator (QMLE) to detect and locate multiple volatility shifts. Our Gaussian QMLE is shown to be consistent under suitable conditions and the rate of convergence is provided. It is also shown that the binary segmentation procedure provides a consistent estimation for the number of volatility shifts. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：50 / 60

页数：11

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