השוואת שיטות

	DCC-GARCH (Dynamic Conditional Correlation)	מודל אוטורגרסיה וקטורית (VAR)
תחום	מימון	אקונומטריקה
משפחה	Regression model	Regression model
שנת המקור	2002	2005
הוגה השיטה	Robert F. Engle	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
סוג	Multivariate volatility model	Multivariate time-series model
מקור מכונן	Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
כינויים	dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
קשורות	5	4
תקציר	DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.	Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).