เปรียบเทียบวิธี

	แบบจำลอง DCC-GARCH (Dynamic Conditional Correlation)	แบบจำลอง ARCH (Autoregressive Conditional Heteroskedasticity)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2002	1982
ผู้ริเริ่ม	Robert F. Engle	Robert F. Engle
ประเภท	Multivariate volatility model	Conditional volatility 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.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
ชื่อเรียกอื่น	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
ที่เกี่ยวข้อง	5	6
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.	The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.