IDEAS home Printed from https://ideas.repec.org/p/ipe/ipetds/1241.html
   My bibliography  Save this paper

Impact of Macro Shocks on Sovereign Default Probabilities

Author

Listed:
  • Marco S. Matsumura

Abstract

We use macro finance models to study the interaction between macro variables and the Brazilian sovereign yield curve using daily data. We calculate the model implied default probabilities and a measure of the impact of macro shocks on the probabilities. An extension of the Dai-Singleton identification strategy for Gaussian models with latent and observable factors is described in order to estimate our models. Among the tested variables, VIX is the most important macro factor affecting short term bonds and default probabilities and the Fed short rate is the most important factor affecting the long term default probabilities.

Suggested Citation

  • Marco S. Matsumura, 2006. "Impact of Macro Shocks on Sovereign Default Probabilities," Discussion Papers 1241, Instituto de Pesquisa Econômica Aplicada - IPEA.
  • Handle: RePEc:ipe:ipetds:1241
    as

    Download full text from publisher

    File URL: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_1241.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Marcello Pericoli & Marco Taboga, 2008. "Canonical Term-Structure Models with Observable Factors and the Dynamics of Bond Risk Premia," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1471-1488, October.
    2. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    3. Darrell Duffie & Lasse Heje Pedersen & Kenneth J. Singleton, 2003. "Modeling Sovereign Yield Spreads: A Case Study of Russian Debt," Journal of Finance, American Finance Association, vol. 58(1), pages 119-159, February.
    4. Leland, Hayne E, 1994. " Corporate Debt Value, Bond Covenants, and Optimal Capital Structure," Journal of Finance, American Finance Association, vol. 49(4), pages 1213-1252, September.
    5. 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.
    6. Andrew Ang & Sen Dong & Monika Piazzesi, 2005. "No-arbitrage Taylor rules," Proceedings, Federal Reserve Bank of San Francisco.
    7. Leland, Hayne E & Toft, Klaus Bjerre, 1996. " Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Journal of Finance, American Finance Association, vol. 51(3), pages 987-1019, July.
    8. Marcos S. Matsumura & Ajax R. B. Moreira, 2006. "Macro Factors and the Brazilian Yield Curve With no Arbitrage Models," Discussion Papers 1210, Instituto de Pesquisa Econômica Aplicada - IPEA.
    9. Pearson, Neil D & Sun, Tong-Sheng, 1994. " Exploiting the Conditional Density in Estimating the Term Structure: An Application to the Cox, Ingersoll, and Ross Model," Journal of Finance, American Finance Association, vol. 49(4), pages 1279-1304, September.
    10. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    11. 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.
    12. Marco Matsumara & Ajax R.B. Moreira, 2005. "Can Macroeconomic Variables Account for the Term Structure of Sovereign Spreads? Studying the Brazilian Case," Discussion Papers 1106, Instituto de Pesquisa Econômica Aplicada - IPEA.
    13. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    14. Darrell Duffie & Rui Kan, 1996. "A Yield-Factor Model Of Interest Rates," Mathematical Finance, Wiley Blackwell, vol. 6(4), pages 379-406.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:ipe:ipetds:1241. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Fabio Schiavinatto). General contact details of provider: http://edirc.repec.org/data/ipeaabr.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.