EconPapers    
Economics at your fingertips  
 

Forecasting Value-at-Risk using block structure multivariate stochastic volatility models

Manabu Asai, Massimiliano Caporin and Michael McAleer

International Review of Economics & Finance, 2015, vol. 40, issue C, 40-50

Abstract: Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose is to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets can be very large. A contribution to this strand of the literature including a block-type parameterization for multivariate stochastic volatility models is provided. The empirical analysis on stock returns on the US market shows that 1% and 5% Value-at-Risk thresholds based on one-step-ahead forecasts of covariances by the new specification are satisfactory for the period including the Global Financial Crisis.

Keywords: Block structures; Multivariate stochastic volatility; Leverage effects; Multi-factors; Heavy-tailed distribution (search for similar items in EconPapers)
JEL-codes: C10 C32 C51 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S105905601500026X
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Forecasting Value-at-Risk using Block Structure Multivariate Stochastic Volatility Models (2013) Downloads
Working Paper: Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models (2012) Downloads
Working Paper: Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models (2012) Downloads
Working Paper: Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models (2012) Downloads
Working Paper: Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models (2012) Downloads
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:eee:reveco:v:40:y:2015:i:c:p:40-50

DOI: 10.1016/j.iref.2015.02.004

Access Statistics for this article

International Review of Economics & Finance is currently edited by H. Beladi and C. Chen

More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2024-05-07
Handle: RePEc:eee:reveco:v:40:y:2015:i:c:p:40-50