Improving the asymmetric stochastic volatility model with ex-post volatility: the identification of the asymmetry. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Zhang, Zehua; Zhao, Ran
• Is Part Of: Quantitative finance. Volume 23:Issue 1(2023)
• Page Start: 35
• Page End: 51
• Publication Date: 2023-01-02
• Subjects: Asymmetric stochastic volatility -- Leverage effect -- Time-varying asymmetry -- Bayesian MCMC -- Density forecasting -- Realized volatility measures; C11 -- C15 -- C22 -- C52; Finance -- Periodicals; Business mathematics -- Periodicals; Finance -- Mathematical models -- Periodicals; Investments -- Mathematics -- Periodicals; Economics -- Periodicals; Finances -- Modèles mathématiques -- Périodiques; 332.015118
• DOI: 10.1080/14697688.2022.2140700
• Languages: English
• ISSNs: 1469-7688

Abstract

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 .