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Support vector machines with evolutionary feature selection for default prediction

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  • Härdle, Wolfgang Karl
  • Prastyo, Dedy Dwi
  • Hafner, Christian

Abstract

Predicting default probabilities is at the core of credit risk management and is becoming more and more important for banks in order to measure their client's degree of risk, and for firms to operate successfully. The SVM with evolutionary feature selection is applied to the CreditReform database. We use classical methods such as discriminan analysis (DA), logit and probit models as benchmark On overall, GA-SVM is outperforms compared to the benchmark models in both training and testing dataset.

Suggested Citation

  • Härdle, Wolfgang Karl & Prastyo, Dedy Dwi & Hafner, Christian, 2012. "Support vector machines with evolutionary feature selection for default prediction," SFB 649 Discussion Papers 2012-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2012-030
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    References listed on IDEAS

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    2. Zieba, Maciej & Härdle, Wolfgang Karl, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers 2016-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Härdle, Wolfgang Karl & Prastyo, Dedy Dwi, 2013. "Default risk calculation based on predictor selection for the Southeast Asian industry," SFB 649 Discussion Papers 2013-037, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Dedy Dwi Prastyo & Härdle, Wolfgang Karl, 2014. "Localising forward intensities for multiperiod corporate default," SFB 649 Discussion Papers 2014-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    More about this item

    Keywords

    SVM; Genetic algorithm; global optmimum; default prediction;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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