IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v36y2012i6p1604-1615.html
   My bibliography  Save this article

Portfolio credit-risk optimization

Author

Listed:
  • Iscoe, Ian
  • Kreinin, Alexander
  • Mausser, Helmut
  • Romanko, Oleksandr

Abstract

This paper evaluates several alternative formulations for minimizing the credit risk of a portfolio of financial contracts with different counterparties. Credit risk optimization is challenging because the portfolio loss distribution is typically unavailable in closed form. This makes it difficult to accurately compute Value-at-Risk (VaR) and expected shortfall (ES) at the extreme quantiles that are of practical interest to financial institutions. Our formulations all exploit the conditional independence of counterparties under a structural credit risk model. We consider various approximations to the conditional portfolio loss distribution and formulate VaR and ES minimization problems for each case. We use two realistic credit portfolios to assess the in- and out-of-sample performance for the resulting VaR- and ES-optimized portfolios, as well as for those which we obtain by minimizing the variance or the second moment of the portfolio losses. We find that a Normal approximation to the conditional loss distribution performs best from a practical standpoint.

Suggested Citation

  • Iscoe, Ian & Kreinin, Alexander & Mausser, Helmut & Romanko, Oleksandr, 2012. "Portfolio credit-risk optimization," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1604-1615.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:6:p:1604-1615
    DOI: 10.1016/j.jbankfin.2012.01.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426612000283
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbankfin.2012.01.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. David Saunders & Costas Xiouros & Stavros Zenios, 2007. "Credit risk optimization using factor models," Annals of Operations Research, Springer, vol. 152(1), pages 49-77, July.
    3. Alexander, S. & Coleman, T.F. & Li, Y., 2006. "Minimizing CVaR and VaR for a portfolio of derivatives," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 583-605, February.
    4. 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.
    5. Tilke, Stephan, 2006. "Reducing Asset Weights' Volatility by Importance Sampling in Stochastic Credit Portfolio Optimization," University of Regensburg Working Papers in Business, Economics and Management Information Systems 417, University of Regensburg, Department of Economics.
    6. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    7. Rudi Zagst & Jan Kehrbaum & Bernd Schmid, 2003. "Portfolio Optimization Under Credit Risk," Computational Statistics, Springer, vol. 18(3), pages 317-338, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nielsen, Caren Yinxia, 2016. "Banks' Credit-Portfolio Choices and Risk-Based Capital Regulation," Working Papers 2016:9, Lund University, Department of Economics.
    2. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    3. Yinxia Nielsen, Caren, 2015. "Banks’ credit-portfolio choices and riskbased capital regulation," Knut Wicksell Working Paper Series 2015/8, Lund University, Knut Wicksell Centre for Financial Studies.
    4. Changqing Luo & Mengzhen Li & Zisheng Ouyang, 2016. "An empirical study on the correlation structure of credit spreads based on the dynamic and pair copula functions," China Finance Review International, Emerald Group Publishing Limited, vol. 6(3), pages 284-303, August.
    5. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    6. Wu, Dexiang & Dash Wu, Desheng, 2019. "An enhanced decision support approach for learning and tracking derivative index," Omega, Elsevier, vol. 88(C), pages 63-76.
    7. Dawen Yan & Xiaohui Zhang & Mingzheng Wang, 2021. "A robust bank asset allocation model integrating credit-rating migration risk and capital adequacy ratio regulations," Annals of Operations Research, Springer, vol. 299(1), pages 659-710, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    2. Hsieh, Chung-Chi & Lu, Yu-Ting, 2010. "Manufacturer's return policy in a two-stage supply chain with two risk-averse retailers and random demand," European Journal of Operational Research, Elsevier, vol. 207(1), pages 514-523, November.
    3. Soleimani, Hamed & Govindan, Kannan, 2014. "Reverse logistics network design and planning utilizing conditional value at risk," European Journal of Operational Research, Elsevier, vol. 237(2), pages 487-497.
    4. Yuichi Takano & Keisuke Nanjo & Noriyoshi Sukegawa & Shinji Mizuno, 2015. "Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs," Computational Management Science, Springer, vol. 12(2), pages 319-340, April.
    5. E. G. Birgin & J. M. Martínez, 2016. "On the application of an Augmented Lagrangian algorithm to some portfolio problems," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(1), pages 79-92, February.
    6. Ahmadi-Javid, Amir & Fallah-Tafti, Malihe, 2019. "Portfolio optimization with entropic value-at-risk," European Journal of Operational Research, Elsevier, vol. 279(1), pages 225-241.
    7. Amir Ahmadi-Javid & Malihe Fallah-Tafti, 2017. "Portfolio Optimization with Entropic Value-at-Risk," Papers 1708.05713, arXiv.org.
    8. Friedrich, Stefan & Paul, Carola & Brandl, Susanne & Biber, Peter & Messerer, Katharina & Knoke, Thomas, 2019. "Economic impact of growth effects in mixed stands of Norway spruce and European beech – A simulation based study," Forest Policy and Economics, Elsevier, vol. 104(C), pages 65-80.
    9. Bedi, Prateek & Nashier, Tripti, 2020. "On the investment credentials of Bitcoin: A cross-currency perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
    10. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    11. Ke Zhou & Jiangjun Gao & Duan Li & Xiangyu Cui, 2017. "Dynamic mean–VaR portfolio selection in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1631-1643, October.
    12. Malavasi, Matteo & Ortobelli Lozza, Sergio & Trück, Stefan, 2021. "Second order of stochastic dominance efficiency vs mean variance efficiency," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1192-1206.
    13. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    14. Roman, Diana & Mitra, Gautam & Zverovich, Victor, 2013. "Enhanced indexation based on second-order stochastic dominance," European Journal of Operational Research, Elsevier, vol. 228(1), pages 273-281.
    15. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    16. Arouri, Mohamed & M’saddek, Oussama & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2019. "Cojumps and asset allocation in international equity markets," Journal of Economic Dynamics and Control, Elsevier, vol. 98(C), pages 1-22.
    17. Vladimir Rankovic & Mikica Drenovak & Branko Uroševic & Ranko Jelic, 2016. "Mean Univariate-GARCH VaR Portfolio Optimization: Actual Portfolio Approach," CESifo Working Paper Series 5731, CESifo.
    18. Harris, Richard D.F. & Mazibas, Murat, 2013. "Dynamic hedge fund portfolio construction: A semi-parametric approach," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 139-149.
    19. Fermanian, Jean-David & Scaillet, Olivier, 2005. "Sensitivity analysis of VaR and Expected Shortfall for portfolios under netting agreements," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 927-958, April.
    20. Allen, D.E. & McAleer, M.J. & Powell, R.J. & Singh, A.K., 2015. "Down-side Risk Metrics as Portfolio Diversification Strategies across the GFC," Econometric Institute Research Papers EI2015-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    More about this item

    Keywords

    Credit risk; Optimization; Portfolio optimization; Risk modeling; Value-at-Risk; Expected shortfall;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:36:y:2012:i:6:p:1604-1615. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.