IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/7078.html
   My bibliography  Save this paper

Risky Swaps

Author

Listed:
  • Gikhman, Ilya

Abstract

In [10] we presented a reduced form of risky bond pricing. At default date, a bond seller fails to continue fulfilling his obligation and the price of the bond sharply drops. For nodefault scenarios, if the face value of the defaulted bond is $1 then the bond price just after the default is its’ recovery rate (RR). Rating agencies and theoretical models are trying to predict RR for companies or sovereign countries. The main theoretical problem with a risky bond or with the general debt problems is presenting the price, knowing the RR. The problem of a credit default swap (CDS) pricing is somewhat an adjacent problem. Recall that the corporate bond price inversely depends on interest rate. In case of a default, the credit risk on a debt investment is related to the loss. There is a possibility for a risky bond buyer to reduce his credit risk. This can be achieved through buying a protection from a protection seller. The bondholder would pay a fixed premium up to maturity or default, which ever one comes first. If default comes before maturity, the protection buyer will receive the difference between the initial face value of the bond and RR. This difference is called ‘loss given default’. This contract represents CDS. The counterparty that pays a fixed premium is called CDS buyer or protection buyer; the opposite party is the CDS seller. Note, that in contrast to corporate bond, CDS contract does not assume that the buyer of the CDS is the holder of underlying bond. Also note that underlying to the swap can be any asset. It is called a reference asset or a reference entity. Thus, CDS is a credit instrument that separates credit risk from corresponding underlying entity. The formal type of the CDS can be described as follows. The buyer of the credit swap pays fixed rate or coupon until maturity or default in case it occurs before the maturity. If default does occur, protection buyer delivers cash or a default asset in exchange with the face value of the defaulted debt. These are known as cash or physical settlements.

Suggested Citation

  • Gikhman, Ilya, 2008. "Risky Swaps," MPRA Paper 7078, University Library of Munich, Germany, revised 31 Mar 2008.
    • Handle: RePEc:pra:mprapa:7078
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/7078/1/MPRA_paper_7078.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    2. 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.
    3. ilya, gikhman, 2005. "Options valuation," MPRA Paper 1452, University Library of Munich, Germany.
    4. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    5. Ilya, Gikhman, 2007. "Corporate debt pricing I," MPRA Paper 1450, University Library of Munich, Germany.
    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. Ilya, Gikhman, 2008. "Multiple risky securities valuation I," MPRA Paper 34511, University Library of Munich, Germany, revised 2011.

    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. Jeremy Leake, 2003. "Credit spreads on sterling corporate bonds and the term structure of UK interest rates," Bank of England working papers 202, Bank of England.
    2. Augusto Castillo, 2004. "Firm and Corporate Bond Valuation: A Simulation Dynamic Programming Approach," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 345-360.
    3. John Y. Campbell & Glen B. Taksler, 2003. "Equity Volatility and Corporate Bond Yields," Journal of Finance, American Finance Association, vol. 58(6), pages 2321-2350, December.
    4. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2011. "A Random Matrix Approach to Credit Risk," Papers 1102.3900, arXiv.org, revised Jun 2011.
    5. 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.
    6. Kraft, Holger & Steffensen, Mogens, 2008. "How to invest optimally in corporate bonds: A reduced-form approach," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 348-385, February.
    7. Hamerle, Alfred & Knapp, Michael & Wildenauer, Nicole, 2005. "Auswirkungen unterschiedlicher Assetkorrelationen in Mehr-Sektoren-Kreditportfoliomodellen," University of Regensburg Working Papers in Business, Economics and Management Information Systems 409, University of Regensburg, Department of Economics.
    8. Jobst, Norbert J. & Zenios, Stavros A., 2005. "On the simulation of portfolios of interest rate and credit risk sensitive securities," European Journal of Operational Research, Elsevier, vol. 161(2), pages 298-324, March.
    9. Maciej Firla-Cuchra, 2005. "Explaining Launch Spreads on Structured Bonds," Economics Series Working Papers 230, University of Oxford, Department of Economics.
    10. Samuel Chege Maina, 2011. "Credit Risk Modelling in Markovian HJM Term Structure Class of Models with Stochastic Volatility," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2011, March.
    11. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    12. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.
    13. Wilson Sy, 2007. "A Causal Framework for Credit Default Theory," Research Paper Series 204, Quantitative Finance Research Centre, University of Technology, Sydney.
    14. Pasquale De Luca, 2017. "The Company Fundamental Analysis and the Default Risk Ratio," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(10), pages 1-79, September.
    15. Yildirim, Yildiray, 2006. "Modeling default risk: A new structural approach," Finance Research Letters, Elsevier, vol. 3(3), pages 165-172, September.
    16. Ramiro Sosa Navarro, 2010. "Fiscal Imbalances, Inflation and Sovereign Default Dynamics," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 1(4), pages 108-142, Octubre.
    17. Hayne E. Leland., 1998. "Agency Costs, Risk Management, and Capital Structure," Research Program in Finance Working Papers RPF-278, University of California at Berkeley.
    18. Reza Kazemi & Ali Mosleh, 2012. "Improving Default Risk Prediction Using Bayesian Model Uncertainty Techniques," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1888-1900, November.
    19. Elisa Di Febo & Eliana Angelini, 2018. "The Relevance of Market Variables in the CDS Spread Volatility: An Empirical Post-crisis Analysis," Global Business Review, International Management Institute, vol. 19(6), pages 1462-1477, December.
    20. Nguyen, Ha, 2023. "An empirical application of Particle Markov Chain Monte Carlo to frailty correlated default models," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 103-121.

    More about this item

    Keywords

    Derivatives; credit derivatives; credit default swap; total return swap; credit linked note; constant maturity default swap; equity default swap; asset swap;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:pra:mprapa:7078. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.