Asymmetric Multivariate Stochastic Volatility
Manabu Asai and
Michael McAleer
Econometric Reviews, 2006, vol. 25, issue 2-3, 453-473
Abstract:
This paper proposes and analyses two types of asymmetric multivariate stochastic volatility (SV) models, namely, (i) the SV with leverage (SV-L) model, which is based on the negative correlation between the innovations in the returns and volatility, and (ii) the SV with leverage and size effect (SV-LSE) model, which is based on the signs and magnitude of the returns. The paper derives the state space form for the logarithm of the squared returns, which follow the multivariate SV-L model, and develops estimation methods for the multivariate SV-L and SV-LSE models based on the Monte Carlo likelihood (MCL) approach. The empirical results show that the multivariate SV-LSE model fits the bivariate and trivariate returns of the S&P 500, the Nikkei 225, and the Hang Seng indexes with respect to AIC and BIC more accurately than does the multivariate SV-L model. Moreover, the empirical results suggest that the univariate models should be rejected in favor of their bivariate and trivariate counterparts.
Keywords: Asymmetric leverage; Bayesian Markov chain Monte Carlo; Dynamic leverage; Importance sampling; Multivariate stochastic volatility; Numerical likelihood; Size effect (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (65)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/07474930600712913 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Asymmetric Multivariate Stochastic Volatility (2005) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:25:y:2006:i:2-3:p:453-473
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/LECR20
DOI: 10.1080/07474930600712913
Access Statistics for this article
Econometric Reviews is currently edited by Dr. Essie Maasoumi
More articles in Econometric Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by ().