Work

Semiparametric Estimation and Application of Realized GARCH Model with Time-Varying Leverage Effect

Year: 2025

Type: article

Abstract: To describe the stylized features of volatility comprehensively, this paper embeds the time-varying leverage effect of volatility into the Realized Generalized AutoRegressive Conditional Heteroskedasticity (RG) model and proposes a new volatility model with a time-varying leverage effect. The Quasi-Maximum Likelihood-Kernel (QML-K) method is proposed to approximate the density function of returns and to estimate the parameters in the new model. Under some mild regularity conditions, the asymptotic properties of the resulting estimators are achieved. Simulation studies demonstrate that the proposed model yields better performances than traditional RG models under different situations. Finally, the empirical analysis shows better finite sample performance of the estimation method and the new model on real data compared with existing methods.

Source: Mathematics

DOI: 10.3390/math13091506

Authors: Jinguan Lin, Yizhi Mao, Hongxia Hao, Guangying Liu

Institution: Nanjing Audit University

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: National Natural Science Foundation of China