Factor Overnight GARCH-Itô Models

被引:0
作者
Kim, Donggyu [1 ]
Oh, Minseog [1 ]
Song, Xinyu [2 ]
Wang, Yazhen [3 ]
机构
[1] Korea Adv Inst Sci & Technol, Coll Business, Seoul, South Korea
[2] Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
[3] Univ Wisconsin Madison, Dept Stat, Madison, WI USA
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
Factor model; High dimensionality; POET; Quasi-maximum likelihood estimation; Realized volatility matrix estimator; Overnight risk; C13; C32; C53; C55; C58; VOLATILITY MATRIX ESTIMATION; MICROSTRUCTURE NOISE; COVARIANCE-MATRIX; FREQUENCY; NUMBER; TIME; JUMPS;
D O I
10.1093/jjfinec/nbad032
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This article introduces a unified factor overnight GARCH-Ito model for large volatility matrix estimation and prediction. To account for whole-day market dynamics, the proposed model has two different instantaneous factor volatility processes for the open-to-close and close-to-open periods, while each embeds the discrete-time multivariate GARCH model structure. To estimate latent factor volatility, we assume the low rank plus sparse structure and employ nonparametric estimation procedures. Then, based on the connection between the discrete-time model structure and the continuous-time diffusion process, we propose a weighted least squares estimation procedure with the non-parametric factor volatility estimator and establish its asymptotic theorems.
引用
收藏
页码:1209 / 1235
页数:27
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