Hypothesis testCausality

Hiemstra-Jones Nonlinear Granger Causality Test

The 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.

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Sources

  1. Hiemstra, 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: 10.1111/j.1540-6261.1994.tb04776.x

Related methods

ScholarGateHiemstra-Jones Causality (Hiemstra-Jones Nonlinear Granger Causality Test). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/hiemstra-jones-causality