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Modeling loss given default with stochastic collateral

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  • Frontczak, Robert
  • Rostek, Stefan

Abstract

This article addresses to the appropriate modeling of loss given default (LGD) for the retail business sector. We assume small or mid-size loans that are assigned in a standardized way and collateralized by residential or commercial property. The focus on this specific type of loans entails two major advantages: Firstly, reduction of complexity is followed by easier-to-grasp methodology and increased handiness of results when comparing with other recent approaches in the field. Secondly, the focussing allows to take into account the characteristic properties of the housing market and its underlying uncertainty and so choose a tailor-made modeling for the collateral. The choice of an exponential Ornstein–Uhlenbeck diffusion as the stochastic process of the collateral combines the desirable features with the charm of analytical solvability which seems to be of advantage as regards acceptance among practitioners. Further key improvements of this approach are the explicit consideration of loan ranking, the disentanglement of the time of default and the time of liquidation as well as the introduction of liquidation cost.

Suggested Citation

  • Frontczak, Robert & Rostek, Stefan, 2015. "Modeling loss given default with stochastic collateral," Economic Modelling, Elsevier, vol. 44(C), pages 162-170.
  • Handle: RePEc:eee:ecmode:v:44:y:2015:i:c:p:162-170
    DOI: 10.1016/j.econmod.2014.10.006
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    3. Miller, Patrick & Töws, Eugen, 2018. "Loss given default adjusted workout processes for leases," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 189-201.
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    5. Yuta Tanoue & Satoshi Yamashita & Hideaki Nagahata, 2020. "Comparison study of two-step LGD estimation model with probability machines," Risk Management, Palgrave Macmillan, vol. 22(3), pages 155-177, September.
    6. Xia, Yufei & Zhao, Junhao & He, Lingyun & Li, Yinguo & Yang, Xiaoli, 2021. "Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1590-1613.
    7. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
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    9. Shi, Baofeng & Chi, Guotai & Li, Weiping, 2020. "Exploring the mismatch between credit ratings and loss-given-default: A credit risk approach," Economic Modelling, Elsevier, vol. 85(C), pages 420-428.
    10. Michela Pelizza & Klaus R. Schenk-Hoppé, 2020. "Pricing Defaulted Italian Mortgages," JRFM, MDPI, vol. 13(2), pages 1-14, February.
    11. Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2017. "Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond," Journal of Financial Stability, Elsevier, vol. 28(C), pages 1-15.
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    13. Guangyou Zhou & Yijia Zhang & Sumei Luo, 2018. "P2P Network Lending, Loss Given Default and Credit Risks," Sustainability, MDPI, vol. 10(4), pages 1-15, March.

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