Kiel Working Papers, Kiel Institute for World Economics
No 1594:
Flexible and Robust Modelling of Volatility Comovements: A Comparison of Two Multifractal Models
Ruipeng Liu and Thomas Lux
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; (follow links to similar papers)
JEL-Codes: C11,; C13,; G15; (follow links to similar papers)
32 pages, February 2010
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