Factor Overnight GARCH-Itô Models

Author:

Kim Donggyu1ORCID,Oh Minseog1,Song Xinyu2ORCID,Wang Yazhen3

Affiliation:

1. College of Business, Korea Advanced Institute of Science and Technology , Seoul, South Korea

2. School of Statistics and Management, Shanghai University of Finance and Economics , Shanghai, China

3. Department of Statistics, University of Wisconsin–Madison , Madison, Wisconsin, USA

Abstract

Abstract This article introduces a unified factor overnight GARCH-Itô 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.

Funder

National Research Foundation of Korea

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Economics and Econometrics,Finance

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