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Non-homogeneous volatility correlations in the bivariate multifractal model
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.
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Journal
European journal of financeVolume
21Issue
12Pagination
971 - 991Publisher
Taylor and FrancisLocation
London, Eng.Publisher DOI
ISSN
1351-847XeISSN
1466-4364Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, Taylor & FrancisUsage metrics
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