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Clustering techniques applied to outlier detection of financial market series using a moving window filtering algorithm

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  • Puigvert Gutiérrez, Josep Maria
  • Fortiana Gregori, Josep

Abstract

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into account the daily behaviour of the market; each of these series is an element of a cluster that represents a different segment of the market. We set up a framework of possible algorithm parameter combinations that detect most of the outliers by market segment. In addition, the algorithm parameters that have been found can also be used to detect outliers in other series with similar economic behaviour in the same cluster. Moreover, the crosschecking of the behaviour of different series within each cluster reduces the possibility of observations being misclassified as outliers. JEL Classification: C19, C49, G19

Suggested Citation

  • Puigvert Gutiérrez, Josep Maria & Fortiana Gregori, Josep, 2008. "Clustering techniques applied to outlier detection of financial market series using a moving window filtering algorithm," Working Paper Series 948, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:2008948
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    References listed on IDEAS

    as
    1. Jurgen A. Doornik & Marius Ooms, 2005. "Outlier Detection in GARCH Models," Tinbergen Institute Discussion Papers 05-092/4, Tinbergen Institute.
    2. Leon Korobow & David P. Stuhr, 1991. "Using cluster analysis as a tool for economic and financial analysis," Research Paper 9132, Federal Reserve Bank of New York.
    3. Seth A. Greenblatt, 1994. "Wavelets in Econometrics: An Application to Outlier Testing," Econometrics 9410001, University Library of Munich, Germany.
    4. Kok, Christoffer & Puigvert Gutiérrez, Josep Maria, 2006. "Euro area banking sector integration: using hierarchical cluster analysis techniques," Working Paper Series 627, European Central Bank.
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    More about this item

    Keywords

    cluster analysis; financial market; moving filtering window algorithm; outliers;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • G19 - Financial Economics - - General Financial Markets - - - Other

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