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Forecasting the insolvency of US banks using support vector machines (SVMs) based on local learning feature selection

Author

Listed:
  • Theophilos Papadimitriou
  • Periklis Gogas
  • Vasilios Plakandaras
  • John C. Mourmouris

Abstract

We propose a support vector machine (SVM)-based structural model to forecast the collapse of banking institutions in the USA using publicly disclosed information from their financial statements on a four-year rolling window. In our approach, the optimum input variable set is defined from a large data set using an iterative relevance-based selection procedure. We train an SVM model to classify banks as solvent and insolvent. The resulting model exhibits significant ability in bank default forecasting.

Suggested Citation

  • Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras & John C. Mourmouris, 2013. "Forecasting the insolvency of US banks using support vector machines (SVMs) based on local learning feature selection," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 3(1/2), pages 83-90.
    • Handle: RePEc:ids:ijcome:v:3:y:2013:i:1/2:p:83-90
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    Cited by:

    1. Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2019. "Predicting European bank stress tests: Survival of the fittest," Global Finance Journal, Elsevier, vol. 39(C), pages 44-57.
    2. Theophilos Papadimitriou & Periklis Gogas & Anna Agrapetidou, 2022. "The resilience of the U.S. banking system," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2819-2835, July.
    3. Santosh Kumar Shrivastav & P. Janaki Ramudu, 2020. "Bankruptcy Prediction and Stress Quantification Using Support Vector Machine: Evidence from Indian Banks," Risks, MDPI, vol. 8(2), pages 1-22, May.
    4. Gogas, Periklis & Papadimitriou, Theophilos & Agrapetidou, Anna, 2018. "Forecasting bank failures and stress testing: A machine learning approach," International Journal of Forecasting, Elsevier, vol. 34(3), pages 440-455.

    More about this item

    Keywords

    bank insolvency; SVM; support vector machines; local learning; feature selection; insolvency forecasting; US banks; USA; United States; banking industry; financial statements; bank default; banking collapse.;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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