So sánh phương pháp

	Mô hình DCC-GARCH (Dynamic Conditional Correlation)	Các mô hình Copula (Gaussian, t, Clayton, Gumbel, Frank)	Lý thuyết Giá trị Cực biên (EVT)
Lĩnh vực	Tài chính	Tài chính	Tài chính
Họ	Regression model	Regression model	Regression model
Năm ra đời	2002	1959	2001
Người khởi xướng	Robert F. Engle	Sklar (1959); dependence-concept treatment by Joe (1997)	Coles (textbook treatment); McNeil, Frey & Embrechts
Loại	Multivariate volatility model	Dependence model	Tail / extreme-event model
Công trình gốc	Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350.	Sklar, A. (1959). Fonctions de répartition à n dimensions et leurs marges. Publications de l'Institut Statistique de l'Université de Paris, 8, 229-231.	Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598
Tên gọi khác	dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon	copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank)	EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold
Liên quan	5	5	5
Tóm tắt	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.	Copula models are a family of functions that describe the dependence structure between variables separately from their individual (marginal) distributions. The foundation is Sklar's theorem (1959), which shows that any multivariate distribution can be split into its marginals plus a copula; Joe (1997) developed the modern catalogue of dependence concepts. They are central to portfolio risk and credit modelling.	Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold.