IDEAS home Printed from https://ideas.repec.org/p/hhs/gunwpe/0685.html
   My bibliography  Save this paper

Cds Index Options Under Incomplete Information

Author

Listed:
  • Herbertsson, Alexander

    (Department of Economics, School of Business, Economics and Law, Göteborg University)

  • Frey, Rüdiger

    (Not stated)

Abstract

We derive practical formulas for CDS index spreads in a credit risk model under incomplete information. The factor process driving the default intensities is not directly observable, and the filtering model of Frey & Schmidt (2012) is used as our setup. In this framework we find a computationally tractable expressions for the payoff of a CDS index option which naturally includes the so-called armageddon correction. A lower bound for the price of the CDS index option is derived and we provide explicit conditions on the strike spread for which this inequality becomes an equality. The bound is computationally feasible and do not depend the noise parameters in the filtering model. We outline how to explicitly compute the quantities involved in the lower bound for the price of the credit index option as well as implement and calibrate this model to market data. A numerical study is performed where we show that the lower bound in our model can be several hundred percent bigger compared with models which assume that the CDS index spreads follows a log-normal process. Also a systematic study is performed in order to understand the impact of various model parameters on CDS index options (and on the index itself).

Suggested Citation

  • Herbertsson, Alexander & Frey, Rüdiger, 2016. "Cds Index Options Under Incomplete Information," Working Papers in Economics 685, University of Gothenburg, Department of Economics.
    • Handle: RePEc:hhs:gunwpe:0685
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/2077/50947
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rüdiger Frey & Wolfgang Runggaldier, 2010. "Pricing credit derivatives under incomplete information: a nonlinear-filtering approach," Finance and Stochastics, Springer, vol. 14(4), pages 495-526, December.
    2. Claudio Fontana & Wolfgang J. Runggaldier, 2010. "Credit Risk And Incomplete Information: Filtering And Em Parameter Estimation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 13(05), pages 683-715.
    3. Rüdiger Frey & Thorsten Schmidt, 2012. "Pricing and hedging of credit derivatives via the innovations approach to nonlinear filtering," Finance and Stochastics, Springer, vol. 16(1), pages 105-133, January.
    4. Giuseppe Di Graziano & L. C. G. Rogers, 2009. "A Dynamic Approach To The Modeling Of Correlation Credit Derivatives Using Markov Chains," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 45-62.
    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. Prakash Chakraborty & Kiseop Lee, 2022. "Bond Prices Under Information Asymmetry and a Short Rate with Instantaneous Feedback," Methodology and Computing in Applied Probability, Springer, vol. 24(2), pages 613-634, June.
    2. Branger, Nicole & Kraft, Holger & Meinerding, Christoph, 2014. "Partial information about contagion risk, self-exciting processes and portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 18-36.
    3. Viviana Fanelli & Claudio Fontana & Francesco Rotondi, 2023. "A hidden Markov model for statistical arbitrage in international crude oil futures markets," Papers 2309.00875, arXiv.org, revised Sep 2024.
    4. Çetin, Umut, 2012. "On absolutely continuous compensators and nonlinear filtering equations in default risk models," Stochastic Processes and their Applications, Elsevier, vol. 122(11), pages 3619-3647.
    5. Ruediger Frey & Lars Roesler & Dan Lu, 2017. "Corporate Security Prices in Structural Credit Risk Models with Incomplete Information: Extended Version," Papers 1701.04780, arXiv.org, revised May 2017.
    6. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    7. Ceci, Claudia & Colaneri, Katia & Cretarola, Alessandra, 2017. "Unit-linked life insurance policies: Optimal hedging in partially observable market models," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 149-163.
    8. Claudia Ceci & Katia Colaneri & Alessandra Cretarola, 2013. "Local risk-minimization under restricted information to asset prices," Papers 1312.4385, arXiv.org, revised Nov 2014.
    9. Claudia Ceci & Katia Colaneri & Alessandra Cretarola, 2016. "Unit-linked life insurance policies: optimal hedging in partially observable market models," Papers 1608.07226, arXiv.org, revised Dec 2016.
    10. Robert Elliott & Jia Shen, 2015. "Credit risk and contagion via self-exciting default intensity," Annals of Finance, Springer, vol. 11(3), pages 319-344, November.
    11. Luca Galimberti & Anastasis Kratsios & Giulia Livieri, 2022. "Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis," Papers 2210.13300, arXiv.org, revised May 2023.
    12. Ceci, Claudia & Cretarola, Alessandra & Russo, Francesco, 2014. "BSDEs under partial information and financial applications," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2628-2653.
    13. Claudia Ceci & Katia Colaneri & Alessandra Cretarola, 2015. "The F\"ollmer-Schweizer decomposition under incomplete information," Papers 1511.05465, arXiv.org, revised Mar 2016.
    14. Yinghui Dong & Kam C. Yuen & Guojing Wang & Chongfeng Wu, 2016. "A Reduced-Form Model for Correlated Defaults with Regime-Switching Shot Noise Intensities," Methodology and Computing in Applied Probability, Springer, vol. 18(2), pages 459-486, June.
    15. Delia Coculescu & Gabriele Visentin, 2017. "A default system with overspilling contagion," Papers 1709.09255, arXiv.org, revised May 2023.
    16. Balakrishna, B S, 2010. "Levy Subordinator Model: A Two Parameter Model of Default Dependency," MPRA Paper 26274, University Library of Munich, Germany.
    17. Branger, Nicole & Grüning, Patrick & Kraft, Holger & Meinerding, Christoph, 2013. "Asset pricing under uncertainty about shock propagation," SAFE Working Paper Series 34, Leibniz Institute for Financial Research SAFE.
    18. Njike Leunga, Charles Guy & Hainaut, Donatien, 2019. "Interbank Credit Risk Modelling with Self-Exciting Jump Processes," LIDAM Discussion Papers ISBA 2019017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Balakrishna, B S, 2010. "Levy Subordinator Model of Default Dependency," MPRA Paper 21386, University Library of Munich, Germany.
    20. Wen-Qiong Liu & Wen-Li Huang, 2019. "Hedging Of Synthetic Cdo Tranches With Spread And Default Risk Based On A Combined Forecasting Approach," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(02), pages 1-17, March.

    More about this item

    Keywords

    Credit risk; CDS index; CDS index options; intensity-based models; dependence modelling; incomplete information; nonlinear filtering; numerical methods;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:hhs:gunwpe:0685. 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: Jessica Oscarsson (email available below). General contact details of provider: https://edirc.repec.org/data/naiguse.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.