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投稿e-mail: jbnuns_sub@bnu.edu.cn

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标题

MRS-GARCH 模型在沪深股指波动中的应用研究

作者

王 娟 李 锐

机构

内蒙古财经大学统计与数学学院;)北京航空航天大学经济管理学院;北京师范大学经济与工商管理学院

摘要

考虑MRS-GARCH 模型中存在的“路径依赖”问题,采用混合Gibbs抽样与EM 算法的两步MCEM-MCML 法求参数的极大似然估计,避免了对原模型的简化或近似而导致的信息损失及估计精度下降.以上证综指和深圳成指日 (周)收益数据为样本,利用MRS-GARCH 模型对沪深股市收益波动进行估计.结果表明:沪深股市存在显著的高、低波 动状态,处于低波动状态的可能性更大,持续时间更长.与MS、Gray及Klassen模型相比,MRS-GARCH 模型估计的波 动状态持续性有所降低.比较各模型的BIC值,MRS-GARCH 模型的拟合性能最优.

关键词

MRS-GARCH 模型;Gibbs抽样;EM 算法;极大似然估计;股市波动

引用

王 娟,李 锐. MRS-GARCH 模型在沪深股指波动中的应用研究[J]. 北京师范大学学报(自然科学版),2015,51(5):484-491.

基金

国家自然科学基金资助项目(71133001)

分类号

O212

DOI

10.16360/j.cnki.jbnuns.2015.05.010

Title

Application of MRS-GARCH Model in Volatility Estimation of China’s Stock Market

Author

WANG Juan, LI Ru

Affiliations

School of Statistics and Mathematics, Inner Mongolia University of Finance and Economics; School of Economic and Management, Beihang University; Business School, Beijing Normal University

Abstract

Due to the existence of path dependent problem in MRS-GARCH models, it is impossible to obtain MLE without resorting to modification of the model. We use a two step MCEM-MCML method combined with Gibbs sampling and EM algorithm to obtain maximum likelihood estimator without any modification of the model. Return series of Shanghai Composite Index and Shen Zhen Component Index are chosen as our sample. Estimation results of MRS-GARCH model suggest significantly high volatility and low volatility states in China’s stock market. The duration for low volatility state is longer. Compared with MS model, Gray’s model and Klaassen’s model, estimation of regime persistence is reduced for MRS-GARCH model. Furthermore, MRS-GARCH model is the best among GARCH model, Gray’s model and Klaassen’s model according to BIC for both data sets.

Key words

MRS-GARCH model; Gibbs sampling; EM algorithm; Maximum likelihood estimation; Volatility of stock market

cite

WANG Juan, LI Ru . Application of MRS-GARCH Model in Volatility Estimation of China’s Stock Market [J]. Journal of Beijing Normal University(Natural Science),2015,51(5):484-491.

DOI

10.16360/j.cnki.jbnuns.2015.05.010

Copyright © 2014 Journal of Beijing Normal University (Natural Science)
Designed by Mr. Sun Chumin. Email: cmsun@mail.bnu.edu.cn