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Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach

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  • Silvia Figini
  • Roberto Savona
  • Marika Vezzoli

Abstract

Focusing on credit risk modelling, this paper introduces a novel approach for ensemble modelling based on a normative linear pooling. Models are first classified as dominant and competitive, and the pooling is run using the competitive models only. Numerical experiments based on parametric (logit, Bayesian model averaging) and nonparametric (classification tree, random forest, bagging, boosting) model comparison shows that the proposed ensemble performs better than alternative approaches, in particular when different modelling cultures are mixed together (logit and classification tree). Copyright © 2016 John Wiley & Sons, Ltd.

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  • Silvia Figini & Roberto Savona & Marika Vezzoli, 2016. "Corporate Default Prediction Model Averaging: A Normative Linear Pooling Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 6-20, January.
    • Handle: RePEc:wly:isacfm:v:23:y:2016:i:1-2:p:6-20
    DOI: 10.1002/isaf.1387
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    References listed on IDEAS

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    2. Salim Lahmiri, 2017. "A two‐step system for direct bank telemarketing outcome classification," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(1), pages 49-55, January.
    3. Paritosh Navinchandra Jha & Marco Cucculelli, 2021. "A New Model Averaging Approach in Predicting Credit Risk Default," Risks, MDPI, vol. 9(6), pages 1-15, June.
    4. Parimal Kumar Giri & Sagar S. De & Sachidananda Dehuri & Sung‐Bae Cho, 2021. "Biogeography based optimization for mining rules to assess credit risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 35-51, January.
    5. Salim Lahmiri & Stelios Bekiros & Anastasia Giakoumelou & Frank Bezzina, 2020. "Performance assessment of ensemble learning systems in financial data classification," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 3-9, January.
    6. Salim Lahmiri, 2016. "Features selection, data mining and finacial risk classification: a comparative study," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(4), pages 265-275, October.

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