A component model for dynamic correlations

被引：237

作者：

Colacito, Riccardo ^{[2
]}

Engle, Robert F. ^{[3
]}

Ghysels, Eric ^{[1
,2
]}

机构：

[1] Univ N Carolina, Dept Econ, Chapel Hill, NC 27599 USA

[2] Univ N Carolina, Kenan Flagler Business Sch, Div Finance, Chapel Hill, NC 27599 USA

[3] NYU, Stern Sch Business, Dept Finance, New York, NY 10003 USA

来源：

JOURNAL OF ECONOMETRICS | 2011年 / 164卷 / 01期

关键词：

Dynamic correlations; Forecasting; Mixed data sampling; CONDITIONAL CORRELATION; RETURN COMOVEMENTS; ASYMPTOTIC THEORY; STOCK;

D O I：

10.1016/j.jeconom.2011.02.013

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We propose a model of dynamic correlations with a short- and long-run component specification, by extending the idea of component models for volatility. We call this class of models DCC-MIDAS. The key ingredients are the Engle (2002) DCC model, the Engle and Lee (1999) component GARCH model replacing the original DCC dynamics with a component specification and the Engle et al. (2006) GARCHMIDAS specification that allows us to extract a long-run correlation component via mixed data sampling. We provide a comprehensive econometric analysis of the new class of models, and provide extensive empirical evidence that supports the model's specification. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：45 / 59

页数：15

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