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Extreme Value Theory Filtering Techniques for Outlier Detection

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Author Info
Jose Olmo () (Department of Economics, City University, London)

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Abstract

We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outlying observations infinite samples. Our tests have nontrivial power for detecting outliers for general forms of the parent distribution and can be implemented when this is unknown and needs to be estimated. Using these techniques this article also develops an algorithm to uncover outliers masked by the presence of influential observations.

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File URL: http://www.city.ac.uk/economics/dps/discussion_papers/0909.pdf
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Publisher Info
Paper provided by Department of Economics, City University, London in its series City University Economics Discussion Papers with number 09/09.

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Length: 19 pages
Date of creation: Jul 2009
Date of revision:
Handle: RePEc:cty:dpaper:0909

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Web page: http://www.city.ac.uk/economics
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Related research
Keywords: Extreme value theory; Hypothesis tests; Outlier detection; Power function; Robust estimation.;

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Armelle Guillou & Peter Hall, 2001. "A diagnostic for selecting the threshold in extreme value analysis," Journal Of The Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 293-305. [Downloadable!] (restricted)
  2. Jurgen A. Doornik & Marius Ooms, 2005. "Outlier Detection in GARCH Models," Tinbergen Institute Discussion Papers 05-092/4, Tinbergen Institute. [Downloadable!]
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  3. Basmann, Robert L., 2003. "Statistical outlier analysis in litigation support: the case of Paul F. Engler and Cactus Feeders, Inc., v. Oprah Winfrey et al," Journal of Econometrics, Elsevier, vol. 113(1), pages 159-200, March. [Downloadable!] (restricted)
  4. Jose Olmo & Jesus Gonzalo, 2004. "Which Extreme Values are Really Extremes?," Econometric Society 2004 North American Winter Meetings 144, Econometric Society. [Downloadable!]
    Other versions:
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This page was last updated on 2009-11-17.

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