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コピュラモデル(正規分布、t分布、Clayton、Gumbel、Frank)×ヨハンセンの共和分検定とベクトル誤差修正モデル×
分野ファイナンスファイナンス
系統Regression modelRegression model
提唱年19591991
提唱者Sklar (1959); dependence-concept treatment by Joe (1997)Søren Johansen
種類Dependence modelMultivariate cointegration / vector error correction model
原典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. link ↗Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗
別名copulas, dependence copulas, vine copulas, Kopula Modelleri (Gaussian, t, Clayton, Gumbel, Frank)Johansen test, VECM, vector error correction model, multivariate cointegration
関連53
概要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.The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.
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ScholarGate手法を比較: Copula Models · Johansen Cointegration Test. 2026-06-17に以下より取得 https://scholargate.app/ja/compare