Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices

时间:2018-04-10浏览:33设置

ShanghaiTech SEM Working Paper No. 2018-005

  

Xin Jin

Shanghai University of Finance and Economics - School of Economics

John M. Maheu

McMaster University - DeGroote School of Business

Qiao Yang

ShanghaiTech University - School of Entrepreneurship and Management


  

Abstract

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. ...


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Keywords: in nite hidden Markov model, Dirichlet process mixture, inverse-Wishart, predictive density, high-frequency data

JEL Classification: G17, C11, C14, C32, C58

  

Date Written: September 2017

  

Available at SSRN: http://ssrn.com/abstract=3159716

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