Dynamic Conditional Correlation: On properties and estimation

Gian Piero Aielli ()
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Gian Piero Aielli: University of Padova

No 142, "Marco Fanno" Working Papers from Dipartimento di Scienze Economiche "Marco Fanno"

Abstract: We address some issues that arise with the Dynamic Conditional Correlation (DCC) model. We prove that the DCC large system estimator (DCC estimator) can be inconsistent, and that the traditional interpretation of the DCC correlation parameters can lead to misleading conclusions. We then suggest a more tractable dynamic conditional correlation model (cDCC model). A related large system estimator (cDCC estimator) is described and heuristically proven to be consistent. Sufficient stationarity conditions for cDCC processes of interest, including the covariance-return process, are established. The DCC and cDCC estimators are compared by means of applications to simulated and real data.

Keywords: Multivariate GARCH Model; Quasi-Maximum-Likelihood; Two-step Estimation; Integrated Correlation; Generalized Profile Likelihood. (search for similar items in EconPapers)
JEL-codes: C13 C32 C51 C52 C53 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2011-11
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:pad:wpaper:0142

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