Department of Economics and Business Economics

Weak diffusion limits of dynamic conditional correlation models

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Christian M. Hafner, Universite Catholique de Louvain
  • ,
  • Sebastien Laurent, Université Aix-Marseille
  • ,
  • Francesco Violante

The properties of dynamic conditional correlation (DCC) models, introduced more than a decade ago, are still not entirely known. This paper fills one of the gaps by deriving weak diffusion limits of a modified version of the classical DCC model. The limiting system of stochastic differential equations is characterized by a diffusion matrix of reduced rank. The degeneracy is due to perfect collinearity between the innovations of the volatility and correlation dynamics. For the special case of constant conditional correlations, a nondegenerate diffusion limit can be obtained. Alternative sets of conditions are considered for the rate of convergence of the parameters, obtaining time-varying but deterministic variances and/or correlations. A Monte Carlo experiment confirms that the often used quasi-approximate maximum likelihood (QAML) method to estimate the diffusion parameters is inconsistent for any fixed frequency, but that it may provide reasonable approximations for sufficiently large frequencies and sample sizes.

Original languageEnglish
JournalEconometric Theory
Volume33
Issue3
Pages (from-to)691-716
Number of pages26
ISSN0266-4666
DOIs
Publication statusPublished - 2017

See relations at Aarhus University Citationformats

ID: 104676811