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Hiemstra-Jonesin epälineaarinen Granger-kausaalisuustesti×Granger-kausaatiotesti×
TieteenalaEkonometriaEkonometria
MenetelmäperheHypothesis testRegression model
Syntyvuosi19941969
KehittäjäCraig Hiemstra & Jonathan JonesClive W. J. Granger
TyyppiNonparametric hypothesis testTime-series predictive causality test
AlkuperäislähdeHiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price-volume relation. The Journal of Finance, 49(5), 1639–1664. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
RinnakkaisnimetHJ Nonlinear Causality Test, Hiemstra-Jones Test, Nonlinear Granger Causality (Hiemstra-Jones), HJ Nedensellik TestiGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Liittyvät35
TiivistelmäThe Hiemstra-Jones test, introduced in 1994, is a nonparametric procedure for detecting nonlinear causal relationships between two time series after removing their linear interdependencies. Developed in the context of stock price and trading volume dynamics, it extends the standard linear Granger causality framework by using correlation integral statistics to detect predictability arising from nonlinear mechanisms that linear VAR models cannot capture.The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.
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ScholarGateVertaile menetelmiä: Hiemstra-Jones Causality · Granger Causality. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare