The Faculty Digital Archive (New York University) · 2009 · 308 citations · 27 references
Open access
Social SciencesEconomicsFinanceEconometricsFinancial EconomicsTime Series AnalysisAsset Return ModelingModel SpecificationTime Series EconometricsTime Series ForecastingVolatility AnalysisVolatility ModelingComponent ModelsCorrelation DynamicsEconometric IdentificationGeneralized Autoregressive Conditional Heteroskedasticity ModelsPositive DefinitenessTime Series Volatility ModelingTime-varying Volatility DynamicsTime-varying Volatility Models
The idea of component models for volatility is extended to dynamic correlations. We propose a model of dynamic correlations with a short- and long-run component specification. We call this class of models DCC-MIDAS as the key ingredients are a combination of the Engle (2002) DCC model, the Engle and Lee (1999) component GARCH model to replace the original DCC dynamics with a component specification and the Engle, Ghysels, and Sohn (2006) GARCH-MIDAS component 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, including conditions for positive semi-definiteness, and provide extensive empirical evidence that supports the model specification.
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