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Analysis of Recovery Rate of Non-Performing Consumer Credit


Markus Hoechstoetter, Abdolreza Nazemi, Svetlozar T. Rachev, Caslav Bozic



Veröffentlichung: 2012 Juli
Art der Veröffentlichung: SIAM Conference on Financial Mathematics & Engineering, Book of Abstracts
BibTex-ID: hoechstoetter2012
BibTeX

Kurzfassung
[[Abstract::There have been more studies on recovery rate modeling of bonds than on recovery rate modeling of personal loans and retail credit. Little to no research have been conducted on recovery rates in non-performing retail credit with emphasis on third-party buyers. From an empirical point of view, in order to analyze the recovery rate distributions across the different industries, over nine million defaulted or nonperforming consumer credit data provided by a German debt collection company are used. A variety of statistical and data mining methods will be examined with respect to prediction and classification. A two-stage model which first classifies debts as extreme or non-extreme with respect to recovery rate is applied; then, the extreme debts are classified into full payment and non-payment. Moreover, the non-extreme recovery rates are predicted in the entire unit interval [0,1]]]

Download: Media:SIAM Abstracts Bozic.pdf
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Forschungsgruppe

Komplexitätsmanagement


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