Weak Diffusion Limits of Dynamic Conditional Correlation Models

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.

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Document type	Article de périodique (Journal article) – Article de recherche
Access type	Accès restreint
Publication date	2017
Language	Anglais
Journal information	"Econometric Theory" - Vol. 33, p. 691-716 (2017)
Peer reviewed	yes
Publisher	Cambridge University Press (Cambridge)
issn	0266-4666
e-issn	1469-4360
Publication status	Publié
Affiliations	UCL - SSH/LIDAM/CORE - Center for operations research and econometrics UCL - SSH/LIDAM/ISBA - Institut de Statistique, Biostatistique et Sciences Actuarielles
Links	https://www.cambridge.org/core/journals/econometric-theory/article/weak-diffusion-limits-of-dynamic-conditional-correlation-models/A9CFEBE0372FDCA1D856189B284E2008 http://hdl.handle.net/2078.1/180490[Handle] https://doi.org/10.1017/S0266466616000128[DOI]

See also
	[boreal:173539]	Weak Diffusion Limits of Dynamic Conditional Correlation Models