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Non-homogeneous volatility correlations in the bivariate multifractal model

journal contribution
posted on 01.01.2015, 00:00 authored by Ruipeng LiuRuipeng Liu, T Lux
In this paper, we consider an extension of the recently proposed bivariate Markov-switching multifractal model of Calvet, Fisher, and Thompson [2006. "Volatility Comovement: A Multifrequency Approach." Journal of Econometrics {131}: 179-215]. In particular, we allow correlations between volatility components to be non-homogeneous with two different parameters governing the volatility correlations at high and low frequencies. Specification tests confirm the added explanatory value of this specification. In order to explore its practical performance, we apply the model for computing value-at-risk statistics for different classes of financial assets and compare the results with the baseline, homogeneous bivariate multifractal model and the bivariate DCC-GARCH of Engle [2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models." Journal of Business & Economic Statistics 20 (3): 339-350]. As it turns out, the multifractal model with heterogeneous volatility correlations provides more reliable results than both the homogeneous benchmark and the DCC-GARCH model. © 2014 Taylor & Francis.

History

Journal

European journal of finance

Volume

21

Issue

12

Pagination

971 - 991

Publisher

Taylor and Francis

Location

London, Eng.

ISSN

1351-847X

eISSN

1466-4364

Language

eng

Publication classification

C Journal article; C1 Refereed article in a scholarly journal

Copyright notice

2014, Taylor & Francis