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Nakajima, J., & Omori, Y. (2009). Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models. Computational Statistics & Data Analysis, 53, 2335-2353.
https://doi.org/10.1016/j.csda.2008.03.015

has been cited by the following article:

• TITLE: The Asymmetry of Shanghai Composite Index Volatility—Stochastic Volatility Models Based on GHST Distribution

  AUTHORS: Xu Han, Jihong Kong

  KEYWORDS: Asymmetric Stochastic Volatility Model, Asymmetry, Gibbs Sampling, Shanghai Composite Index, VaR Risk Measurement

  JOURNAL NAME: Open Journal of Social Sciences, Vol.8 No.12, December 28, 2020

  ABSTRACT: In this paper, we analyzed how the asymmetric stochastic volatility models with GHST distribution capture the asymmetry of stock index volatility in China. Under the setting of fat-tail distribution, we introduced the correlation parameter ρ of two error terms to refine the classification of ASV model from two aspects of Contemporaneous correlation and Subsequent correlation. So we could compare the effect of ASV model in demonstrating the asymmetry of stock index volatility under the above different settings. Using the daily returns of Shanghai stock composite index, we concluded that the ASV model with GHST distribution and Subsequent correlation between error terms can better describe the asymmetry of the stock index in China. The DIC value and Kupiec test verified the adequacy and the effectiveness of risk measurement of the above model respectively.