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The Tail that Wags the Dog: Integrating Credit Risk in Asset Portfolios

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  • NORBERT J. JOBST
  • STAVROS A. ZENIOS

Abstract

Tails are of paramount importance in shaping the risk profile of portfolios with credit risk sensitive securities. In this context risk management tools require simulations that accurately capture the tails, and optimization models that limit tail effects. Ignoring the tails in the simulation or using inadequate optimization metrics can have significant effects and destroy portfolio efficiency. The resulting portfolio risk profile can be grossly misrepresented when long run performance is optimized without consideration of the short term tail effects. This paper illustrates the pitfalls and suggests models for avoiding them.
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Suggested Citation

  • Norbert J. Jobst & Stavros A. Zenios, 2001. "The Tail that Wags the Dog: Integrating Credit Risk in Asset Portfolios," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 3(1), pages 31-43, April.
  • Handle: RePEc:eme:jrfpps:eb043481
    DOI: 10.1108/eb043481
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    References listed on IDEAS

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    1. René M. Stulz, 1996. "Rethinking Risk Management," Journal of Applied Corporate Finance, Morgan Stanley, vol. 9(3), pages 8-25, September.
    2. Gordon M. Bodnar & Gregory S. Hayt & Richard C. Marston, 1998. "1998 Wharton Survey of Financial Risk Management by US Non-Financial Firms," Financial Management, Financial Management Association, vol. 27(4), Winter.
    3. Norbert Jobst & Stavros A. Zenios, 2001. "Extending Credit Risk (Pricing) Models for the Simulation of Portfolios of Interest Rate and Credit Risk Sensitive Securities," Center for Financial Institutions Working Papers 01-25, Wharton School Center for Financial Institutions, University of Pennsylvania.
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    Cited by:

    1. Rui Zhou & Daniel P. Palomar, 2020. "Solving High-Order Portfolios via Successive Convex Approximation Algorithms," Papers 2008.00863, arXiv.org.
    2. Tao Pham Dinh & Yi-Shuai Niu, 2011. "An efficient DC programming approach for portfolio decision with higher moments," Computational Optimization and Applications, Springer, vol. 50(3), pages 525-554, December.
    3. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    4. Bertocchi, Marida & Giacometti, Rosella & Zenios, Stavros A., 2005. "Risk factor analysis and portfolio immunization in the corporate bond market," European Journal of Operational Research, Elsevier, vol. 161(2), pages 348-363, March.
    5. Tatiana Ermolieva & Yuri Ermoliev & Guenther Fischer & Istvan Galambos, 2003. "The Role of Financial Instruments in Integrated Catastrophic Flood Management," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 207-230, September.
    6. Fábián, Csaba I., 2008. "Handling CVaR objectives and constraints in two-stage stochastic models," European Journal of Operational Research, Elsevier, vol. 191(3), pages 888-911, December.
    7. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2002. "CVaR models with selective hedging for international asset allocation," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1535-1561, July.
    8. Michal Kaut & Hercules Vladimirou & Stein W. Wallace & Stavros A. Zenios, 2007. "Stability analysis of portfolio management with conditional value-at-risk," Quantitative Finance, Taylor & Francis Journals, vol. 7(4), pages 397-409.
    9. Jobst, Norbert J. & Mitra, Gautam & Zenios, Stavros A., 2006. "Integrating market and credit risk: A simulation and optimisation perspective," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 717-742, February.
    10. Iscoe, Ian & Kreinin, Alexander & Mausser, Helmut & Romanko, Oleksandr, 2012. "Portfolio credit-risk optimization," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1604-1615.
    11. Andrea Beltratti & Paolo Colla, 2007. "A portfolio-based evaluation of affine term structure models," Annals of Operations Research, Springer, vol. 151(1), pages 193-222, April.

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