[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/fip/fedkrw/rwp13-06.html
   My bibliography  Save this paper

Creditor recovery: the macroeconomic dependence of industry equilibrium

Author

Listed:
  • Nada Mora
Abstract
This paper reconciles industry conditions with the state of the economy in driving asset liquidation values and, therefore, recovery rates on defaulted debt securities. Macroeconomic effects matter but they operate differentially at the industry level.

Suggested Citation

  • Nada Mora, 2013. "Creditor recovery: the macroeconomic dependence of industry equilibrium," Research Working Paper RWP 13-06, Federal Reserve Bank of Kansas City.
  • Handle: RePEc:fip:fedkrw:rwp13-06
    as

    Download full text from publisher

    File URL: https://www.kansascityfed.org/documents/7709/rwp13-06.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:bla:ecnote:v:33:y:2004:i:2:p:183-208 is not listed on IDEAS
    2. Shleifer, Andrei & Vishny, Robert W, 1992. "Liquidation Values and Debt Capacity: A Market Equilibrium Approach," Journal of Finance, American Finance Association, vol. 47(4), pages 1343-1366, September.
    3. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    4. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    5. Daniel M. Covitz & Song Han, 2004. "An empirical analysis of bond recovery rates: exploring a structural view of default," Finance and Economics Discussion Series 2005-10, Board of Governors of the Federal Reserve System (U.S.).
    6. Rajan, Raghuram G & Zingales, Luigi, 1998. "Financial Dependence and Growth," American Economic Review, American Economic Association, vol. 88(3), pages 559-586, June.
    7. Andrei Shleifer & Robert Vishny, 2011. "Fire Sales in Finance and Macroeconomics," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 29-48, Winter.
    8. Paul Asquith & Robert Gertner & David Scharfstein, 1994. "Anatomy of Financial Distress: An Examination of Junk-Bond Issuers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 625-658.
    9. 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.
    10. Heitor Almeida & Thomas Philippon, 2007. "The Risk‐Adjusted Cost of Financial Distress," Journal of Finance, American Finance Association, vol. 62(6), pages 2557-2586, December.
    11. Coval, Joshua & Stafford, Erik, 2007. "Asset fire sales (and purchases) in equity markets," Journal of Financial Economics, Elsevier, vol. 86(2), pages 479-512, November.
    12. Longstaff, Francis A & Schwartz, Eduardo S, 1995. "A Simple Approach to Valuing Risky Fixed and Floating Rate Debt," Journal of Finance, American Finance Association, vol. 50(3), pages 789-819, July.
    13. James, Christopher & Kizilaslan, Atay, 2014. "Asset Specificity, Industry-Driven Recovery Risk, and Loan Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 599-631, June.
    14. Jankowitsch, Rainer & Nagler, Florian & Subrahmanyam, Marti G., 2014. "The determinants of recovery rates in the US corporate bond market," Journal of Financial Economics, Elsevier, vol. 114(1), pages 155-177.
    15. Khieu, Hinh D. & Mullineaux, Donald J. & Yi, Ha-Chin, 2012. "The determinants of bank loan recovery rates," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 923-933.
    16. Schuermann, Til, 2014. "Stress testing banks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 717-728.
    17. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    18. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    19. Jokivuolle, Esa & Virén, Matti, 2013. "Cyclical default and recovery in stress testing loan losses," Journal of Financial Stability, Elsevier, vol. 9(1), pages 139-149.
    20. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
    21. 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.
    22. repec:bla:jfinan:v:53:y:1998:i:3:p:939-978 is not listed on IDEAS
    23. Simon Firestone & Marcelo Rezende, 2013. "Are Banks' Internal Risk Parameters Consistent? Evidence from Syndicated Loans," Finance and Economics Discussion Series 2013-84, Board of Governors of the Federal Reserve System (U.S.).
    24. Nada Mora, 2012. "What determines creditor recovery rates?," Economic Review, Federal Reserve Bank of Kansas City, vol. 97(Q II).
    25. Bennett, Rosalind L. & Unal, Haluk, 2014. "The effects of resolution methods and industry stress on the loss on assets from bank failures," Journal of Financial Stability, Elsevier, vol. 15(C), pages 18-31.
    26. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    27. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
    28. Abraham, Katharine G & Katz, Lawrence F, 1986. "Cyclical Unemployment: Sectoral Shifts or Aggregate Disturbances?," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 507-522, June.
    29. Das, Sanjiv R. & Hanouna, Paul, 2009. "Implied recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1837-1857, November.
    30. Raghuram G. Rajan & Rodney Ramcharan, 2014. "Financial Fire Sales: Evidence from Bank Failures," Finance and Economics Discussion Series 2014-67, Board of Governors of the Federal Reserve System (U.S.).
    31. Efraim Benmelech & Nittai K. Bergman, 2011. "Bankruptcy and the Collateral Channel," Journal of Finance, American Finance Association, vol. 66(2), pages 337-378, April.
    32. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-632, Nov.-Dec..
    33. Thorburn, Karin S., 2000. "Bankruptcy auctions: costs, debt recovery, and firm survival," Journal of Financial Economics, Elsevier, vol. 58(3), pages 337-368, December.
    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. Nazemi, Abdolreza & Fatemi Pour, Farnoosh & Heidenreich, Konstantin & Fabozzi, Frank J., 2017. "Fuzzy decision fusion approach for loss-given-default modeling," European Journal of Operational Research, Elsevier, vol. 262(2), pages 780-791.
    2. Paolo Gambetti & Francesco Roccazzella & Frédéric Vrins, 2022. "Meta-Learning Approaches for Recovery Rate Prediction," Risks, MDPI, vol. 10(6), pages 1-29, June.
    3. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    4. 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).
    5. Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2017. "Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond," Journal of Financial Stability, Elsevier, vol. 28(C), pages 1-15.
    6. Nazemi, Abdolreza & Fabozzi, Frank J., 2024. "Interpretable machine learning for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 164(C).
    7. John, Kose & Mateti, Ravi S. & Vasudevan, Gopala & Amira, Khaled, 2016. "Investor protection and firm value: Evidence from PIPE offerings," Journal of Financial Stability, Elsevier, vol. 26(C), pages 78-89.
    8. Nazemi, Abdolreza & Fabozzi, Frank J., 2018. "Macroeconomic variable selection for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 14-25.
    9. Marc Gürtler & Marvin Zöllner, 2023. "Heterogeneities among credit risk parameter distributions: the modality defines the best estimation method," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 251-287, March.
    10. Juan Pineiro-Chousa & Marcos Vizcaíno-González & Samuel Ribeiro-Navarrete, 2019. "Using voting decisions to identify shocks in the financial services industry," Service Business, Springer;Pan-Pacific Business Association, vol. 13(2), pages 419-431, June.
    11. 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.
    12. Frame, W. Scott & Lazaryan, Nika & McLemore, Ping & Mihov, Atanas, 2024. "Operational loss recoveries and the macroeconomic environment: Evidence from the U.S. banking sector," Journal of Banking & Finance, Elsevier, vol. 165(C).

    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. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    2. Nada Mora, 2012. "What determines creditor recovery rates?," Economic Review, Federal Reserve Bank of Kansas City, vol. 97(Q II).
    3. Khieu, Hinh D. & Mullineaux, Donald J. & Yi, Ha-Chin, 2012. "The determinants of bank loan recovery rates," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 923-933.
    4. Mili, Medhi & Sahut, Jean-Michel & Teulon, Frédéric, 2018. "Modeling recovery rates of corporate defaulted bonds in developed and developing countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 28-44.
    5. Pascal François, 2019. "The Determinants of Market-Implied Recovery Rates," Risks, MDPI, vol. 7(2), pages 1-15, May.
    6. Cangemi, Robert R. & Mason, Joseph R. & Pagano, Michael S., 2012. "Options-based structural model estimation of bond recovery rates," Journal of Financial Intermediation, Elsevier, vol. 21(3), pages 473-506.
    7. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    8. Yao, Xiao & Crook, Jonathan & Andreeva, Galina, 2017. "Is it obligor or instrument that explains recovery rate: Evidence from US corporate bond," Journal of Financial Stability, Elsevier, vol. 28(C), pages 1-15.
    9. Oh, Seungjoon, 2018. "Fire-sale acquisitions and intra-industry contagion," Journal of Corporate Finance, Elsevier, vol. 50(C), pages 265-293.
    10. Zhang, Zhipeng, 2009. "Who Pulls the Plug? Theory and Evidence on Corporate Bankruptcy Decisions," MPRA Paper 17676, University Library of Munich, Germany, revised 05 Oct 2009.
    11. 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.
    12. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    13. Barbagli, Matteo & Vrins, Frédéric, 2023. "Accounting for PD-LGD dependency: A tractable extension to the Basel ASRF framework," Economic Modelling, Elsevier, vol. 125(C).
    14. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, December.
    15. Douglas Gale & Tanju Yorulmazer, 2020. "Bank capital, fire sales, and the social value of deposits," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(4), pages 919-963, June.
    16. Tang, Dragon Yongjun & Yan, Hong, 2010. "Market conditions, default risk and credit spreads," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 743-753, April.
    17. Dinc, Serdar & Erel, Isil & Liao, Rose, 2017. "Fire sale discount: Evidence from the sale of minority equity stakes," Journal of Financial Economics, Elsevier, vol. 125(3), pages 475-490.
    18. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2022. "Corporate Loan Recovery Rates under Downturn Conditions in a Developing Economy: Evidence from Zimbabwe," Risks, MDPI, vol. 10(10), pages 1-24, October.
    19. Frame, W. Scott & Lazaryan, Nika & McLemore, Ping & Mihov, Atanas, 2024. "Operational loss recoveries and the macroeconomic environment: Evidence from the U.S. banking sector," Journal of Banking & Finance, Elsevier, vol. 165(C).
    20. Gambetti, Paolo & Gauthier, Geneviève & Vrins, Frédéric, 2019. "Recovery rates: Uncertainty certainly matters," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 371-383.

    More about this item

    Keywords

    Credit; Risk; Business cycles;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fip:fedkrw:rwp13-06. 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: Zach Kastens (email available below). General contact details of provider: https://edirc.repec.org/data/frbkcus.html .

    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.