Factor Overnight GARCH-Itô Models

Donggyu Kim, Minseog Oh, Xinyu Song and Yazhen Wang

Journal of Financial Econometrics, 2024, vol. 22, issue 5, 1209-1235

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.

Keywords: Factor model; High dimensionality; POET; Quasi-maximum likelihood estimation; Realized volatility matrix estimator; Overnight risk (search for similar items in EconPapers)
JEL-codes: C13 C32 C53 C55 C58 (search for similar items in EconPapers)
Date: 2024
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