เปรียบเทียบวิธี

	แบบจำลอง DCC-GARCH (Dynamic Conditional Correlation)	แบบจำลองการถดถอยอัตโนมัติแบบเวกเตอร์ (VAR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2002	1980
ผู้ริเริ่ม	Robert F. Engle	Christopher A. Sims
ประเภท	Multivariate volatility model	Multivariate time-series model
แหล่งต้นตำรับ	Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
ชื่อเรียกอื่น	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC	VAR, VAR model, vector autoregressive model, multivariate autoregression
ที่เกี่ยวข้อง	5	5
สรุป	The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.