IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v44y2024i1p122-147.html
   My bibliography  Save this article

Leveraging prices from credit and equity option markets for portfolio risk management

Author

Listed:
  • Jean‐François Bégin
  • Mathieu Boudreault
  • Mathieu Thériault

Abstract

This study presents a firm‐specific methodology for extracting implied default intensities and recovery rates jointly from unit recovery claim prices—backed by out‐of‐the‐money put options—and credit default swap premiums, therefore providing time‐varying and market‐consistent views of credit risk at the individual level. We apply the procedure to about 400 firms spanning different sectors of the US economy between 2003 and 2019. The main determinants of default intensities and recovery rates are analyzed with statistical and machine learning methods linking default risk and credit losses to market, sector, and individual variables. Consistent with the literature, we find that individual volatility, leverage, and corporate bond market determinants are key factors explaining the implied default intensities and recovery rates. Then, we apply the framework in the context of credit risk management in applications, like, market‐consistent credit value‐at‐risk calculation and stress testing.

Suggested Citation

  • Jean‐François Bégin & Mathieu Boudreault & Mathieu Thériault, 2024. "Leveraging prices from credit and equity option markets for portfolio risk management," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 122-147, January.
  • Handle: RePEc:wly:jfutmk:v:44:y:2024:i:1:p:122-147
    DOI: 10.1002/fut.22465
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22465
    Download Restriction: no

    File URL: https://libkey.io/10.1002/fut.22465?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
    ---><---

    References listed on IDEAS

    as
    1. Alexander, Carol & Kaeck, Andreas, 2008. "Regime dependent determinants of credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 32(6), pages 1008-1021, June.
    2. Unal, Haluk & Madan, Dilip & Guntay, Levent, 2003. "Pricing the risk of recovery in default with absolute priority rule violation," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1001-1025, June.
    3. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    4. Francis A. Longstaff & Sanjay Mithal & Eric Neis, 2005. "Corporate Yield Spreads: Default Risk or Liquidity? New Evidence from the Credit Default Swap Market," Journal of Finance, American Finance Association, vol. 60(5), pages 2213-2253, October.
    5. Anh Le, 2015. "Separating the Components of Default Risk: A Derivative-Based Approach," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-48.
    6. Bo Young Chang & Greg Orosi, 2020. "A Simple Method for Extracting the Probability of Default from American Put Option Prices," Staff Working Papers 20-15, Bank of Canada.
    7. Elkamhi, Redouane & Jacobs, Kris & Pan, Xuhui, 2014. "The Cross Section of Recovery Rates and Default Probabilities Implied by Credit Default Swap Spreads," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(1), pages 193-220, February.
    8. Jennifer Conrad & Robert F Dittmar & Allaudeen Hameed, 2020. "Implied Default Probabilities and Losses Given Default from Option Prices," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 629-652.
    9. Nazemi, Abdolreza & Heidenreich, Konstantin & Fabozzi, Frank J., 2018. "Improving corporate bond recovery rate prediction using multi-factor support vector regressions," European Journal of Operational Research, Elsevier, vol. 271(2), pages 664-675.
    10. Ericsson, Jan & Jacobs, Kris & Oviedo, Rodolfo, 2009. "The Determinants of Credit Default Swap Premia," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 109-132, February.
    11. Qi, Min & Zhao, Xinlei, 2011. "Comparison of modeling methods for Loss Given Default," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2842-2855, November.
    12. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," The Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    13. 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.
    14. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    15. Nazemi, Abdolreza & Fabozzi, Frank J., 2018. "Macroeconomic variable selection for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 14-25.
    16. Düllmann, Klaus & Trapp, Monika, 2004. "Systematic Risk in Recovery Rates: An Empirical Analysis of US Corporate Credit Exposures," Discussion Paper Series 2: Banking and Financial Studies 2004,02, Deutsche Bundesbank.
    17. Christoph Benkert, 2004. "Explaining credit default swap premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(1), pages 71-92, January.
    18. Doshi, Hitesh & Elkamhi, Redouane & Ornthanalai, Chayawat, 2018. "The Term Structure of Expected Recovery Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(6), pages 2619-2661, December.
    19. Liu, Xiaoquan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2007. "Closed-form transformations from risk-neutral to real-world distributions," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1501-1520, May.
    20. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    21. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    22. Loterman, Gert & Brown, Iain & Martens, David & Mues, Christophe & Baesens, Bart, 2012. "Benchmarking regression algorithms for loss given default modeling," International Journal of Forecasting, Elsevier, vol. 28(1), pages 161-170.
    23. Bo Young Chang & Greg Orosi, 2020. "A simple method for extracting the probability of default from American put option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1535-1547, October.
    24. Fabozzi, Frank J. & Cheng, Xiaolin & Chen, Ren-Raw, 2007. "Exploring the components of credit risk in credit default swaps," Finance Research Letters, Elsevier, vol. 4(1), pages 10-18, March.
    25. Peter Carr & Liuren Wu, 2011. "A Simple Robust Link Between American Puts and Credit Protection," The Review of Financial Studies, Society for Financial Studies, vol. 24(2), pages 473-505.
    26. Bo Young Chang & Greg Orosi, 2017. "Equity Option Implied Probability of Default and Equity Recovery Rate," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(6), pages 599-613, June.
    27. Pascal François & Weiyu Jiang, 2019. "Credit Value Adjustment with Market-implied Recovery," Journal of Financial Services Research, Springer;Western Finance Association, vol. 56(2), pages 145-166, October.
    28. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    29. Hitesh Doshi & Jan Ericsson & Kris Jacobs & Stuart M. Turnbull, 2013. "Pricing Credit Default Swaps with Observable Covariates," The Review of Financial Studies, Society for Financial Studies, vol. 26(8), pages 2049-2094.
    Full references (including those not matched with items on IDEAS)

    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. Pascal François, 2019. "The Determinants of Market-Implied Recovery Rates," Risks, MDPI, vol. 7(2), pages 1-15, May.
    2. Barbagli, Matteo & François, Pascal & Gauthier, Geneviève & Vrins, Frédéric, 2024. "The role of CDS spreads in explaining bond recovery rates," LIDAM Discussion Papers LFIN 2024002, Université catholique de Louvain, Louvain Finance (LFIN).
    3. Schläfer, Timo & Uhrig-Homburg, Marliese, 2014. "Is recovery risk priced?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 257-270.
    4. Augustin, Patrick & Subrahmanyam, Marti G. & Tang, Dragon Yongjun & Wang, Sarah Qian, 2014. "Credit Default Swaps: A Survey," Foundations and Trends(R) in Finance, now publishers, vol. 9(1-2), pages 1-196, December.
    5. Nazemi, Abdolreza & Baumann, Friedrich & Fabozzi, Frank J., 2022. "Intertemporal defaulted bond recoveries prediction via machine learning," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1162-1177.
    6. Hwang, Ruey-Ching & Chu, Chih-Kang & Yu, Kaizhi, 2020. "Predicting LGD distributions with mixed continuous and discrete ordinal outcomes," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1003-1022.
    7. Benbouzid, Nadia & Mallick, Sushanta K. & Sousa, Ricardo M., 2017. "Do country-level financial structures explain bank-level CDS spreads?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 135-145.
    8. Antonio Trujillo-Ponce & Reyes Samaniego-Medina & Clara Cardone-Riportella, 2014. "Examining what best explains corporate credit risk: accounting-based versus market-based models," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(2), pages 253-276, April.
    9. Paolo Gambetti & Francesco Roccazzella & Frédéric Vrins, 2022. "Meta-Learning Approaches for Recovery Rate Prediction," Risks, MDPI, vol. 10(6), pages 1-29, June.
    10. Ruey-Ching Hwang & Chih-Kang Chu & Kaizhi Yu, 2021. "Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality," Journal of Financial Services Research, Springer;Western Finance Association, vol. 59(3), pages 143-172, June.
    11. Jansen, Jeroen & Das, Sanjiv R. & Fabozzi, Frank J., 2018. "Local volatility and the recovery rate of credit default swaps," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 1-29.
    12. Choi, Yong Seok & Doshi, Hitesh & Jacobs, Kris & Turnbull, Stuart M., 2020. "Pricing structured products with economic covariates," Journal of Financial Economics, Elsevier, vol. 135(3), pages 754-773.
    13. Murphy, Austin & Headley, Adrian, 2022. "An empirical evaluation of alternative fundamental models of credit spreads," International Review of Financial Analysis, Elsevier, vol. 81(C).
    14. Benbouzid, Nadia & Leonida, Leone & Mallick, Sushanta K., 2018. "The non-monotonic impact of bank size on their default swap spreads: Cross-country evidence," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 226-240.
    15. Wisniewski, Tomasz Piotr & Lambe, Brendan John, 2015. "Does economic policy uncertainty drive CDS spreads?," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 447-458.
    16. Steven Lecce & Andrew Lepone & Michael D. McKenzie & Jin Boon Wong & Jin Y. Yang, 2018. "Short‐selling and credit default swap spreads—Where do informed traders trade?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(8), pages 925-942, August.
    17. Annaert, Jan & De Ceuster, Marc & Van Roy, Patrick & Vespro, Cristina, 2013. "What determines Euro area bank CDS spreads?," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 444-461.
    18. Distaso, Walter & Roccazzella, Francesco & Vrins, Frédéric, 2023. "Business cycle and realized losses in the consumer credit industry," LIDAM Discussion Papers LFIN 2023007, Université catholique de Louvain, Louvain Finance (LFIN).
    19. Benbouzid, Nadia & Kumar, Abhishek & Mallick, Sushanta K. & Sousa, Ricardo M. & Stojanovic, Aleksandar, 2022. "Bank credit risk and macro-prudential policies: Role of counter-cyclical capital buffer," Journal of Financial Stability, Elsevier, vol. 63(C).
    20. Kellner, Ralf & Nagl, Maximilian & Rösch, Daniel, 2022. "Opening the black box – Quantile neural networks for loss given default prediction," Journal of Banking & Finance, Elsevier, vol. 134(C).

    More about this item

    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:wly:jfutmk:v:44:y:2024:i:1:p:122-147. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    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.