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Pricing Default Events: Surprise, Exogeneity and Contagion

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  • Gouriéroux, C.
  • Monfort, A.
  • Renne, J-P.

Abstract

In order to derive closed-form expressions of the prices of credit derivatives, standard credit-risk models typically price the default intensities, but not the default events themselves. The default indicator is replaced by an appropriate prediction and the prediction error, that is the default-event surprise, is neglected. Our paper develops an approach to get closed-form expressions for the prices of credit derivatives written on multiple names without neglecting default-event surprises. This approach differs from the standard one, since the default counts necessarily cause the factor process under the risk-neutral probability, even if this is not the case under the historical probability. This implies that the standard exponential pricing formula of default does not apply. Using U.S. bond data, we show that allowing for the pricing of default events has important implications in terms of both data-fitting and model-implied physical probabilities of default. In particular, it may provide a solution to the credit spread puzzle. Besides, we show how our approach can be used to account for the propagation of defaults on the prices of credit derivatives.

Suggested Citation

  • Gouriéroux, C. & Monfort, A. & Renne, J-P., 2013. "Pricing Default Events: Surprise, Exogeneity and Contagion," Working papers 455, Banque de France.
  • Handle: RePEc:bfr:banfra:455
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    Cited by:

    1. Christian Gouriéroux & Alain Monfort & Sarah Mouabbi & Jean-Paul Renne, 2021. "Disastrous Defaults [Risk premia and term premia in general equilibrium]," Review of Finance, European Finance Association, vol. 25(6), pages 1727-1772.
    2. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Specification Testing in Hawkes Models," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 139-171.
    3. Francine Gresnigt & Erik Kole & Philip Hans Franses, 2017. "Exploiting Spillovers to Forecast Crashes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 936-955, December.
    4. Gourieroux, Christian & Lu, Yang, 2015. "Love and death: A Freund model with frailty," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 191-203.
    5. Patrick Augustin & Mikhail Chernov & Dongho Song, 2018. "Sovereign Credit Risk and Exchange Rates: Evidence from CDS Quanto Spreads," NBER Working Papers 24506, National Bureau of Economic Research, Inc.
    6. Alain Monfort & Fulvio Pegoraro & Jean-Paul Renne & Guillaume Roussellet, 2021. "Affine Modeling of Credit Risk, Pricing of Credit Events, and Contagion," Management Science, INFORMS, vol. 67(6), pages 3674-3693, June.
    7. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    8. Dumitru, Ana-Maria & Holden, Thomas, 2019. "Quantifying the transmission of European sovereign default risk," EconStor Preprints 193632, ZBW - Leibniz Information Centre for Economics.

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    More about this item

    Keywords

    Credit Derivative; Default Event; Default Intensity; Frailty; Contagion; Credit Spread Puzzle.;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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