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

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters Pub Date : 2025-01-21 DOI:10.1016/j.frl.2025.106808

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

引用次数: 0

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.

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来源期刊

Finance Research Letters BUSINESS, FINANCE-

CiteScore

11.10

自引率

14.40%

发文量

863

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