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Modeling Loss Risk in Loan Portfolios with Various Heterogeneity Factors

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  • Osadchiy, Maksim

Abstract

This paper extends the classical Vasicek credit risk model by introducing a comprehensive multi-factor framework that simultaneously incorporates key sources of portfolio heterogeneity – namely, variations in asset weights, recovery rates, default probabilities, and asset correlations. By modeling the complex interactions among these factors, our approach provides a more realistic and nuanced assessment of loss distributions and risk measures. Monte Carlo simulations demonstrate that the extended Vasicek-style model yields accurate approximations of portfolio Value at Risk (VaR) across portfolios with diverse recovery profiles and moderate concentration levels. This advancement improves the precision of credit risk measurement, addresses current regulatory gaps, and offers a solid foundation for more sophisticated risk management of heterogeneous credit portfolios.

Suggested Citation

  • Osadchiy, Maksim, 2025. "Modeling Loss Risk in Loan Portfolios with Various Heterogeneity Factors," MPRA Paper 127032, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:127032
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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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