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An Automatic Portmanteau Test For Nonlinear Dependence

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  • Grivas, Charisios

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.

Suggested Citation

  • Grivas, Charisios, 2021. "An Automatic Portmanteau Test For Nonlinear Dependence," MPRA Paper 114312, University Library of Munich, Germany, revised 22 Aug 2022.
    • Handle: RePEc:pra:mprapa:114312
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    References listed on IDEAS

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    1. Juan Carlos Escanciano & Ignacio N. Lobato & Lin Zhu, 2013. "Automatic Specification Testing for Vector Autoregressions and Multivariate Nonlinear Time Series Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 426-437, October.
    2. Zacharias Psaradakis & Marián Vávra, 2019. "Portmanteau tests for linearity of stationary time series," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 248-262, February.
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    9. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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