EconPapers    
Economics at your fingertips  
 

Flexible and robust modelling of volatility comovements: a comparison of two multifractal models

Ruipeng Liu and Thomas Lux

No 1594, Kiel Working Papers from Kiel Institute for the World Economy (IfW)

Abstract: Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been introduced as a new tool for modeling financial time series. In this paper, we propose a parsimonious version of a bivariate multifractal model and estimate its parameters via both maximum likelihood and simulation based inference approaches. In order to explore its practical performance, we apply the model for computing value-at-risk and expected shortfall statistics for various portfolios and compare the results with those from an alternative bivariate multifractal model proposed by Calvet et al. (2006) and the bivariate CC-GARCH of Bollerslev (1990). As it turns out, the multifractal models provide much more reliable results than CC-GARCH, and our new model compares well with the one of Calvet et al. although it has an even smaller number of parameters.

Keywords: Long memory; multifractal models; simulation based inference; value-at-risk; expected shortfall (search for similar items in EconPapers)
JEL-codes: C11 C13 G15 (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/30048/1/618788565.pdf (application/pdf)

Related works:
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:zbw:ifwkwp:1594

Access Statistics for this paper

More papers in Kiel Working Papers from Kiel Institute for the World Economy (IfW) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().

 
Page updated 2020-07-07
Handle: RePEc:zbw:ifwkwp:1594