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Robust adaptive rate-optimal testing for the white noise hypothesis

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  • Guay, Alain
  • Guerre, Emmanuel
  • Lazarová, Štěpána

Abstract

A new test is proposed for the weak white noise null hypothesis. The test is based on a new automatic selection of the order for a Box–Pierce (1970) test statistic or the test statistic of Hong (1996). The heteroskedasticity and autocorrelation-consistent (HAC) critical values from Lee (2007) are used, allowing for estimation of the error term. The data-driven order selection is tailored to detect a new class of alternatives with autocorrelation coefficients which can be o(n−1/2) provided there are sufficiently many of such coefficients. A simulation experiment illustrates the good statistical properties of the test both under the weak white noise null and the alternative.

Suggested Citation

  • Guay, Alain & Guerre, Emmanuel & Lazarová, Štěpána, 2013. "Robust adaptive rate-optimal testing for the white noise hypothesis," Journal of Econometrics, Elsevier, vol. 176(2), pages 134-145.
  • Handle: RePEc:eee:econom:v:176:y:2013:i:2:p:134-145
    DOI: 10.1016/j.jeconom.2013.05.001
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    Cited by:

    1. Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.

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    More about this item

    Keywords

    Weak white noise hypothesis; HAC inference; Automatic nonparametric tests; Adaptive rate-optimality;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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