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Generalized Runs Test for the IID Hypothesis

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  • Jin Seo Cho

    () (Department of Economics, Korea University, Seoul, South Korea)

  • Halbert White

    () (Department of Economics, University of California, San Diego, U.S.A.)

Abstract

We provide a familiy of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to test designed for specific alternatives, such as serial correlation, GARCH, or structural breaks. Our tests have appealing computational simplicity in that they do not require kernel density estimation, with the associated challenge of bandwidth selection. Simulations show levels close to nominal asymptotic levels.Our tests have power against both dependent and heterogeneous alternatives, as both theory and simulations demonstrate.

Suggested Citation

  • Jin Seo Cho & Halbert White, 2009. "Generalized Runs Test for the IID Hypothesis," Discussion Paper Series 0913, Institute of Economic Research, Korea University.
  • Handle: RePEc:iek:wpaper:0913
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    File URL: http://econ.korea.ac.kr/~ri/WorkingPapers/w0913.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jin Seo Cho & Jin Seok Park & Sang Woo Park, 2018. "Testing for the Conditional Geometric Mixture Distribution," Working papers 2018rwp-123, Yonsei University, Yonsei Economics Research Institute.
    2. repec:eee:econom:v:202:y:2018:i:1:p:45-56 is not listed on IDEAS
    3. Cho, Jin Seo & Phillips, Peter C.B., 2018. "Pythagorean generalization of testing the equality of two symmetric positive definite matrices," Journal of Econometrics, Elsevier, vol. 202(1), pages 45-56.
    4. Hentati-Kaffel, Rania & de Peretti, Philippe, 2015. "Generalized runs tests to detect randomness in hedge funds returns," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 608-615.

    More about this item

    Keywords

    IID condition; Runs test; Geometric Distribution; Gaussian process; Dependence; Structural Break;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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