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The Instability of the Pearson Correlation Coefficient in the Presence of Coincidental Outliers

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Listed:
  • Yunmi Kim

    (University of Seoul)

  • Tae-Hwan Kim

    (Yonsei University)

  • Tolga Ergun

    (State Street Corporation)

Abstract

It is well known that any statistic based on sample averages can be sensitive to outliers. Some examples are the conventional moments-based statistics such as the sample mean, the sample variance, or the sample covariance of a set of observations on two variables. Given that sample correlation is defined as sample covariance divided by the product of sample standard deviations, one might suspect that the impact of outliers on the correlation coefficient may be neither present nor noticeable because of a ¡®dampening effect¡¯ i.e., the effects of outliers on both the numerator and the denominator of the correlation coefficient can cancel each other. In this paper, we formally investigate this issue. Contrary to such an expectation, we show analytically and by simulations that the distortion caused by outliers in the behavior of the correlation coefficient can be fairly large in some cases, especially when outliers are present in both variables at the same time. These outliers are called ¡®coincidental outliers.¡¯ We consider some robust alternative measures and compare their performance in the presence of such coincidental outliers.

Suggested Citation

  • Yunmi Kim & Tae-Hwan Kim & Tolga Ergun, 2014. "The Instability of the Pearson Correlation Coefficient in the Presence of Coincidental Outliers," Working papers 2014rwp-74, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2014rwp-74
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    References listed on IDEAS

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    1. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    2. Huo, Lijuan & Kim, Tae-Hwan & Kim, Yunmi, 2012. "Robust estimation of covariance and its application to portfolio optimization," Finance Research Letters, Elsevier, vol. 9(3), pages 121-134.
    3. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    4. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
    5. Bonato, Matteo, 2011. "Robust estimation of skewness and kurtosis in distributions with infinite higher moments," Finance Research Letters, Elsevier, vol. 8(2), pages 77-87, June.
    6. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
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    More about this item

    Keywords

    Correlation; robust statistic; outliers;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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