A factor-GARCH model for high dimensional volatilities
Li, Xiao-ling and Li, Yuan and Pan, Jia-zhu and Zhang, Xing-fa (2022) A factor-GARCH model for high dimensional volatilities. Acta Mathematicae Applicatae Sinica, 38 (3). 635–663. ISSN 1618-3932 (https://doi.org/10.1007/s10255-022-1104-6)
Preview |
Text.
Filename: Li_etal_AMAS_2021_A_factor_GARCH_model_for_high_dimensional_volatilities.pdf
Accepted Author Manuscript License: Strathprints license 1.0 Download (1MB)| Preview |
Abstract
This paper proposes a method for modelling volatilities (conditional covariance matrices) of high dimensional dynamic data. We combine the ideas of approximate factor models for dimension reduction and multivariate GARCH models to establish a model to describe the dynamics of high dimensional volatilities. Sparsity condition and thresholding technique are applied to the estimation of the error covariance matrices, and quasi maximum likelihood estimation (QMLE) method is used to estimate the parameters of the common factor conditional covariance matrix. Asymptotic theories are developed for the proposed estimation. Monte Carlo simulation studies and real data examples are presented to support the methodology.
ORCID iDs
Li, Xiao-ling, Li, Yuan, Pan, Jia-zhu ORCID: https://orcid.org/0000-0001-7346-2052 and Zhang, Xing-fa;-
-
Item type: Article ID code: 81383 Dates: DateEvent1 July 2022Published15 December 2021Accepted22 July 2021SubmittedSubjects: Science > Mathematics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 07 Jul 2022 09:49 Last modified: 26 Sep 2024 00:51 URI: https://strathprints.strath.ac.uk/id/eprint/81383