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Two Models of Stochastic Loss Given Default

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  • Simone Farinelli
  • Mykhaylo Shkolnikov

Abstract

We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. The credit losses are integrated into a structural model of default events accounting for correlations between the default events and the associated losses. We show how the models can be calibrated and analyze the impact of correlations between the occurrences of defaults and recoveries by testing our models for a representative sample portfolio.

Suggested Citation

  • Simone Farinelli & Mykhaylo Shkolnikov, 2012. "Two Models of Stochastic Loss Given Default," Papers 1205.5369, arXiv.org, revised May 2012.
  • Handle: RePEc:arx:papers:1205.5369
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    File URL: http://arxiv.org/pdf/1205.5369
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    References listed on IDEAS

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    1. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
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    Cited by:

    1. Matthias Fischer & Thorsten Moser & Marius Pfeuffer, 2018. "A Discussion on Recent Risk Measures with Application to Credit Risk: Calculating Risk Contributions and Identifying Risk Concentrations," Risks, MDPI, vol. 6(4), pages 1-28, December.
    2. Simone Farinelli & Hideyuki Takada, 2014. "Credit Bubbles in Arbitrage Markets: The Geometric Arbitrage Approach to Credit Risk," Papers 1406.6805, arXiv.org, revised Jul 2021.
    3. Janette Larney & Gerrit Lodewicus Grobler & James Samuel Allison, 2022. "Introducing Two Parsimonious Standard Power Mixture Models for Bimodal Proportional Data with Application to Loss Given Default," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    4. Yi-Ping Chang & Jing-Xiu Lin & Chih-Tun Yu, 2016. "Calculating Value-at-Risk Using the Granularity Adjustment Method in the Portfolio Credit Risk Model with Random Loss Given Default," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 12(2), pages 157-176, August.
    5. Annalisa Di Clemente, 2013. "Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2013(109), pages 5-24.
    6. Wolfgang Reitgruber, 2012. "The Calculus of Expected Loss: Backtesting Parameter-Based Expected Loss in a Basel II Framework," Papers 1211.4946, arXiv.org, revised Aug 2013.

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