Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects

• Main Authors: Zhongxian Men, Tony S. Wirjanto, Adam W. Kolkiewicz
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Journal of Risk and Financial Management
• Subjects: Bayesian inference; MCMC; slice sampler
• Online Access: https://www.mdpi.com/1911-8074/14/5/225
• ISSN: 1911-8066; 1911-8074

This paper studies multiscale stochastic volatility models of financial asset returns. It specifies two components in the log-volatility process and allows for leverage/asymmetric effects from both components while return innovation terms follow a heavy/fat tailed Student <i>t</i> distribution. The two components are shown to be important in capturing persistent dependence in return volatility, which is often absent in applications of stochastic volatility models which incorporate leverage/asymmetric effects. The models are applied to asset returns from a foreign currency market and an equity market. The model fits are assessed, and the proposed models are shown to compare favorably to the one-component asymmetric stochastic volatility models with Gaussian and Student <i>t</i> distributed innovation terms.