Abstract
The purpose of the paper is to discuss ten things potential users should know about the limits of the Dynamic Conditional Correlation (DCC) representation for estimating and forecasting time-varying conditional correlations. The reasons given for caution about the use of DCC include the following: DCC represents the dynamic conditional covariances of the standardized residuals, and hence does not yield dynamic conditional correlations; DCC is stated rather than derived; DCC has no moments; DCC does not have testable regularity conditions; DCC yields inconsistent two step estimators; DCC has no asymptotic properties; DCC is not a special case of Generalized Autoregressive Conditional Correlation (GARCC), which has testable regularity conditions and standard asymptotic properties; DCC is not dynamic empirically as the effect of news is typically extremely small; DCC cannot be distinguished empirically from diagonal Baba, Engle, Kraft and Kroner (BEKK) in small systems; and DCC may be a useful filter or a diagnostic check, but it is not a model.
Highlights
The 21st century has seen substantial and growing interest in the analysis of dynamic covariances and correlations across investment instruments
The paper discussed ten things potential users should know about the Dynamic Conditional
The reasons given for being cautious about the use of Dynamic Conditional Correlation (DCC) included the following: DCC represents the dynamic conditional covariances of the standardized residuals, and does not yield dynamic conditional correlations; DCC is stated rather than derived; DCC has no moments; DCC does not have testable regularity conditions; DCC yields inconsistent two step estimators; DCC has no asymptotic properties; DCC is not a special case of Generalized Autoregressive Conditional Correlation (GARCC), which has testable regularity conditions and standard asymptotic properties; DCC is not dynamic empirically as the effect of news is typically extremely small; DCC cannot be distinguished empirically from diagonal BEKK in small systems; and DCC may be a useful filter or a diagnostic check, but it is not a model
Summary
The 21st century has seen substantial and growing interest in the analysis of dynamic covariances and correlations across investment instruments. Despite the growing interest in DCC and its central role in the estimation of dynamic correlations, several important issues relating to this representation seem to have been ignored in the financial econometrics literature These important issues include the absence of any derivation of DCC and its mathematical properties, and a lack of any demonstration of the asymptotic properties of the estimated parameters (for a summary of these issues, see [13]). Most published papers dealing with dynamic correlations do not discuss stationarity of the model, the regularity conditions, or the asymptotic properties of the estimators. Another critical element of DCC is associated with the construction of the dynamic conditional correlations.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
