Enhancing high-dimensional dynamic conditional angular correlation model based on GARCH family models: Comparative performance analysis for portfolio optimization

Zhangshuang Sun, Xuerui Gao, Kangyang Luo, Yanqin Bai, Jiyuan Tao and Guoqiang Wang

Finance Research Letters, 2025, vol. 75, issue C

Abstract: In this paper, we present a novel extension of the dynamic conditional angular correlation framework through several influential GARCH family models. This extension aims to enhance the precision in capturing volatility dynamics and broaden their applicability across diverse market conditions. Furthermore, the application of stock portfolio optimization based on the real financial data is conducted to evaluate and compare the estimation performance of dynamic correlation matrices produced by the different extended models. These experiments reveal the significant superiority of the dynamic conditional angular correlation with fractionally integrated GARCH model in markets exhibiting the long-term memory characteristics, effectively capturing persistent volatility.

Keywords: Covariance matrix estimation; Dynamic conditional correlation; Dynamic conditional angular correlation; GARCH family models; Portfolio optimization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S154461232500073X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:75:y:2025:i:c:s154461232500073x

DOI: 10.1016/j.frl.2025.106808

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().