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Bump Hunting for Risk: a New Data Mining Tool and its Applications

Author

Listed:
  • Ursula Becker

    (University of Munich)

  • Ludwig Fahrmeir

    (University of Munich)

Abstract

Summary Bump Hunting is a new data mining technique (Friedman, J. H. & Fisher, N. I. 1999). In this paper we explore its potential for risk assessment. The method is first presented and illustrated by application to credit risk data from a German bank. Based on comparisons with standard analyses of this data set, we conclude that Bump Hunting has potential for identification of risk in financial applications. In the next step the original Bump Hunting algorithm is modified for analysis of censored survival data. This Survival Bump Hunting is used for the analysis of a bone marrow transplant data set and these results are compared to previous analyses which used standard survival methods such as Cox regression. The findings obtained using Survival Bump Hunting confirmed the previous analyses and added some interesting new aspects.

Suggested Citation

  • Ursula Becker & Ludwig Fahrmeir, 2001. "Bump Hunting for Risk: a New Data Mining Tool and its Applications," Computational Statistics, Springer, vol. 16(3), pages 373-386, September.
    • Handle: RePEc:spr:compst:v:16:y:2001:i:3:d:10.1007_s001800100073
    DOI: 10.1007/s001800100073
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    Cited by:

    1. Polonik, Wolfgang & Wang, Zailong, 2010. "PRIM analysis," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 525-540, March.

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