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An Automatic Portmanteau Test For Nonlinear Dependence

Charisios Grivas ()

MPRA Paper from University Library of Munich, Germany

Abstract: A data-driven version of a portmanteau test for detecting nonlinear types of statistical dependence is considered. An attractive feature of the proposed test is that it properly controls type I error without depending on the number of lags. In addition, the automatic test is found to have higher power in simulations when compared to the McLeod and Li test, for both raw data and residuals.

Keywords: ARMA time series; Akaike's AIC; Schwarz's BIC; Portmanteau test; Data-driven test (search for similar items in EconPapers)
JEL-codes: C01 (search for similar items in EconPapers)
Date: 2021-12-19, Revised 2022-08-22
New Economics Papers: this item is included in nep-ecm and nep-ets
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