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Risk factor contributions in portfolio credit risk models

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  • Rosen, Dan
  • Saunders, David

Abstract

Determining contributions to overall portfolio risk is an important topic in risk management. For positions (instruments and sub-portfolios), this problem has been well studied, and a significant theory built, around the calculation of marginal contributions. We consider the problem of determining the contributions to portfolio risk of risk factors. This cannot be addressed through an immediate extension of techniques for position contributions, since the portfolio loss is a nonlinear function of the risk factors. We employ the Hoeffding decomposition of the portfolio loss into a sum of terms depending on the factors. This decomposition restores linearity, but includes terms arising from joint effects of groups of factors. These cross-factor terms provide information to risk managers, since they can be viewed as best hedges of the portfolio loss involving instruments of increasing complexity. We illustrate the technique on multi-factor portfolio credit risk models, where systematic factors represent industries, geographical sectors, etc.

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  • Rosen, Dan & Saunders, David, 2010. "Risk factor contributions in portfolio credit risk models," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 336-349, February.
    • Handle: RePEc:eee:jbfina:v:34:y:2010:i:2:p:336-349
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    7. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    8. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
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    10. Gary van Vuuren & Riaan de Jongh, 2017. "A comparison of risk aggregation estimates using copulas and Fleishman distributions," Applied Economics, Taylor & Francis Journals, vol. 49(17), pages 1715-1731, April.
    11. Karabey, Uǧur & Kleinow, Torsten & Cairns, Andrew J.G., 2014. "Factor risk quantification in annuity models," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 34-45.
    12. Kao, Lie-Jane, 2015. "A portfolio-invariant capital allocation scheme penalizing concentration risk," Economic Modelling, Elsevier, vol. 51(C), pages 560-570.
    13. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    14. Arvid Raknerud & Bjørn Helge Vatne, 2013. "The relations between bank-funding costs, retail rates, and loan volumes. Evidence form Norwegian microdata," Discussion Papers 742, Statistics Norway, Research Department.
    15. Andreas Tsanakas & Pietro Millossovich, 2016. "Sensitivity Analysis Using Risk Measures," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 30-48, January.
    16. Christoph Frei, 2020. "A New Approach to Risk Attribution and Its Application in Credit Risk Analysis," Risks, MDPI, vol. 8(2), pages 1-13, June.
    17. Marcus C. Christiansen, 2021. "Time-dynamic evaluations under non-monotone information generated by marked point processes," Finance and Stochastics, Springer, vol. 25(3), pages 563-596, July.
    18. Targino, Rodrigo S. & Peters, Gareth W. & Shevchenko, Pavel V., 2015. "Sequential Monte Carlo Samplers for capital allocation under copula-dependent risk models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 206-226.
    19. Regele, Fabian & Gründl, Helmut, 2021. "Asset concentration risk and insurance solvency regulation," ICIR Working Paper Series 40/21, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    20. Kang, Woo-Young & Poshakwale, Sunil, 2019. "A new approach to optimal capital allocation for RORAC maximization in banks," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 153-165.
    21. Miloš Božović, 2021. "Sistemska Komponenta Kreditnog Rizika: Metod Kopula (Systemic Component Of Credit Risk: A Copula-Based Method)," Ekonomske ideje i praksa, Faculty of Economics and Business, University of Belgrade, issue 41, pages 1-13, June.
    22. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    23. Lu, Meng-Jou & Chen, Cathy Yi-Hsuan & Härdle, Karl Wolfgang & Härdle, 2015. "Copula-Based Factor Model for Credit Risk Analysis," SFB 649 Discussion Papers SFB649DP2015-042, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    24. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Hardle, 2020. "Copula-Based Factor Model for Credit Risk Analysis," Papers 2009.12092, arXiv.org, revised Oct 2020.
    25. Laurent, Jean-Paul & Sestier, Michael & Thomas, Stéphane, 2016. "Trading book and credit risk: How fundamental is the Basel review?," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 211-223.

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