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フーリエ DCC-GARCH モデル×ベクトル自己回帰 (VAR)×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年2002 (DCC-GARCH); Fourier extension applied from mid-2010s onward1980
提唱者Engle (2002) for DCC-GARCH; Fourier extension by Gallant (1981) and later applied in financial econometricsChristopher A. Sims
種類Multivariate volatility model with smooth structural breaksMultivariate time-series model
原典Engle, R. (2002). Dynamic conditional correlations: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. link ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
別名Fourier DCC-GARCH, Fourier-augmented DCC-GARCH, DCC-GARCH with Fourier terms, smooth structural break DCC-GARCHVAR, VAR model, vector autoregressive model, multivariate autoregression
関連55
概要The Fourier DCC-GARCH model extends Engle's Dynamic Conditional Correlation GARCH framework by embedding Fourier trigonometric terms in the conditional mean or variance equations. This allows the model to approximate smooth, gradual structural shifts in volatility dynamics and inter-asset correlations without requiring knowledge of the number or timing of break points.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.
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ScholarGate手法を比較: Fourier DCC-GARCH · Vector Autoregression. 2026-06-18に以下より取得 https://scholargate.app/ja/compare