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Bayesian parametric and semiparametric factor models for large realized covariance matrices
2019-08
发表期刊JOURNAL OF APPLIED ECONOMETRICS (IF:2.3[JCR-2023],3.0[5-Year])
ISSN0883-7252
卷号34期号:5页码:641-660
发表状态已发表
DOI10.1002/jae.2685
摘要This paper introduces a new factor structure suitable for modeling large realized covariance matrices with full likelihood-based estimation. Parametric and nonparametric versions are introduced. Because of the computational advantages of our approach, we can model the factor nonparametrically as a Dirichlet process mixture or as an infinite hidden Markov mixture, which leads to an infinite mixture of inverse-Wishart distributions. Applications to 10 assets and 60 assets show that the models perform well. By exploiting parallel computing the models can be estimated in a matter of a few minutes.
收录类别SSCI
语种英语
资助项目NSFC[71773069]
WOS研究方向Business & Economics ; Mathematical Methods In Social Sciences
WOS类目Economics ; Social Sciences, Mathematical Methods
WOS记录号WOS:000478607500002
出版者WILEY
WOS关键词AUTOREGRESSIVE WISHART MODEL
原始文献类型Article
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文献类型期刊论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/61147
专题创业与管理学院_PI研究组_杨乔组
通讯作者Maheu, John M.
作者单位
1.Shanghai Univ Finance & Econ, Sch Econ, Shanghai, Peoples R China
2.McMaster Univ, DeGroote Sch Business, 1280 Main St West, Hamilton, ON L8S 4M4, Canada
3.ShanghaiTech Univ, Sch Entrepreneurship & Management, Shanghai, Peoples R China
推荐引用方式
GB/T 7714
Jin, Xin,Maheu, John M.,Yang, Qiao. Bayesian parametric and semiparametric factor models for large realized covariance matrices[J]. JOURNAL OF APPLIED ECONOMETRICS,2019,34(5):641-660.
APA Jin, Xin,Maheu, John M.,&Yang, Qiao.(2019).Bayesian parametric and semiparametric factor models for large realized covariance matrices.JOURNAL OF APPLIED ECONOMETRICS,34(5),641-660.
MLA Jin, Xin,et al."Bayesian parametric and semiparametric factor models for large realized covariance matrices".JOURNAL OF APPLIED ECONOMETRICS 34.5(2019):641-660.
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