Improving the asymmetric stochastic volatility model with ex-post volatility: the identification of the asymmetry

Zhang, Zehua and Zhao, Ran ORCID: 0000-0001-8502-0024 (2022) Improving the asymmetric stochastic volatility model with ex-post volatility: the identification of the asymmetry. QUANTITATIVE FINANCE, 23 (1). pp. 35-51.

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Official URL: http://dx.doi.org/10.1080/14697688.2022.2140700

Abstract

Simulation studies show that the asymmetry stochastic volatility (ASV) models may infer erroneous correlation coefficients, due to their predetermined return-volatility specification. We propose identifying the correlation parameter by incorporating the ex-post volatility in the ASV framework. We obtain a significantly smaller magnitude in the estimated correlation coefficients between equity and volatility processes among major U.S. equity market indexes. Out-of-sample index return distribution forecasts demonstrate superior performance when jointly estimating the return and the ex-post volatility processes. The corrected return-volatility correlations by estimating proposed ASV models with subsample data further document the time-varying leverage effect.

Item Type:	Article
Uncontrolled Keywords:	Asymmetric stochastic volatility, Bayesian MCMC, Density forecasting, Leverage effect, Realized volatility measures, Time-varying asymmetry
Divisions:	Faculty of Humanities and Social Sciences > School of Management
Depositing User:	Symplectic Admin
Date Deposited:	16 Feb 2023 11:40
Last Modified:	16 Feb 2023 11:40
DOI:	10.1080/14697688.2022.2140700
Open Access URL:	https://doi.org/10.1080/14697688.2022.2140700
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3168435