Nonparametric estimation and inference for conditional density based Granger causality measures

DOI10.1016/j.jeconom.2014.03.001zbMath1293.62082OpenAlexW2064776043WikidataQ130544080 ScholiaQ130544080MaRDI QIDQ2451777

Taoufik Bouezmarni, Abderrahim Taamouti, Anouar El Ghouch

Publication date: 4 June 2014

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://dro.dur.ac.uk/13769/1/13769.pdf

zbMATH Keywords

time seriesexchange ratesnonparametric estimationvolatility indexlocal bootstrapBernstein copula densitycausality measuresdividend-price ratioliquidity stock returns

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Nonparametric estimation (62G05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (5)

CHARACTERISTIC FUNCTION BASED TESTING FOR CONDITIONAL INDEPENDENCE: A NONPARAMETRIC REGRESSION APPROACH ⋮ Asymptotic properties of Bernstein estimators on the simplex ⋮ Inference on local causality and tests of non-causality in time series ⋮ A specification test for dynamic conditional distribution models with function-valued parameters ⋮ Testing for Granger-causality in quantiles

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