手法を比較

	非線形DCC-GARCHモデル（非対称動的条件付き相関）	DCC-GARCHモデル（動学的条件付き相関）
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	2006	2002
提唱者	Cappiello, Engle & Sheppard	Robert F. Engle
種類	Multivariate volatility and correlation model	Multivariate volatility model
原典	Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537–572.	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.
別名	ADCC-GARCH, Asymmetric DCC-GARCH, NL-DCC-GARCH, Nonlinear Asymmetric DCC	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
関連	2	5
概要	The Nonlinear DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation framework by allowing correlations to respond asymmetrically to negative versus positive return shocks. Proposed by Cappiello, Engle, and Sheppard (2006), it is the standard tool for measuring time-varying co-movement and contagion effects in multivariate financial time series when bad news is expected to increase correlations more than good news.	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.