Department of Economics and Business Economics

Weak diffusion limits of dynamic conditional correlation models

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Weak diffusion limits of dynamic conditional correlation models. / Hafner, Christian M.; Laurent, Sebastien; Violante, Francesco.

In: Econometric Theory, Vol. 33, No. 3, 2017, p. 691-716.

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

Harvard

Hafner, CM, Laurent, S & Violante, F 2017, 'Weak diffusion limits of dynamic conditional correlation models', Econometric Theory, vol. 33, no. 3, pp. 691-716. https://doi.org/10.1017/S0266466616000128

APA

CBE

MLA

Hafner, Christian M., Sebastien Laurent, and Francesco Violante. "Weak diffusion limits of dynamic conditional correlation models". Econometric Theory. 2017, 33(3). 691-716. https://doi.org/10.1017/S0266466616000128

Vancouver

Author

Hafner, Christian M. ; Laurent, Sebastien ; Violante, Francesco. / Weak diffusion limits of dynamic conditional correlation models. In: Econometric Theory. 2017 ; Vol. 33, No. 3. pp. 691-716.

Bibtex

@article{fcffb78cfae34b98ab2254f3bc3cee03,
title = "Weak diffusion limits of dynamic conditional correlation models",
abstract = "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.",
author = "Hafner, {Christian M.} and Sebastien Laurent and Francesco Violante",
year = "2017",
doi = "10.1017/S0266466616000128",
language = "English",
volume = "33",
pages = "691--716",
journal = "Econometric Theory",
issn = "0266-4666",
publisher = "Cambridge University Press",
number = "3",

}

RIS

TY - JOUR

T1 - Weak diffusion limits of dynamic conditional correlation models

AU - Hafner, Christian M.

AU - Laurent, Sebastien

AU - Violante, Francesco

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84976539282&partnerID=8YFLogxK

U2 - 10.1017/S0266466616000128

DO - 10.1017/S0266466616000128

M3 - Journal article

AN - SCOPUS:84976539282

VL - 33

SP - 691

EP - 716

JO - Econometric Theory

JF - Econometric Theory

SN - 0266-4666

IS - 3

ER -