IDEAS home Printed from https://ideas.repec.org/p/ucm/doicae/0604.html
   My bibliography  Save this paper

Valor en Riesgo en carteras de renta fija: una comparación entre modelos empíricos de la estructura temporal

Author

Listed:
  • Pilar Abad

    () (Universidad de Barcelona. Departamento de Econometría y Estadística.)

  • Sonia Benito

    () (Universidad Nacional de Educación a Distancia (UNED). Departamento de Análisis Económico II)

Abstract

En este trabajo se compara la precisión de diferentes medidas de Valor en Riesgo (VaR) en carteras de renta fija calculadas a partir de diferentes modelos empíricos multifactoriales de la estructura temporal de los tipos de interés (ETTI). Los modelos incluidos en la comparativa son tres: (1) modelos de regresión, (2) componentes principales y (3) paramétricos. Adicionalmente, se incluye el sistema de cartografía que utiliza Riskmetrics. Dado que el cálculo de las medidas VaR con dichos modelos requiere el uso de una medida de volatilidad, en este trabajo se utilizan tres medidas distintas: medias móviles exponenciales, medias móviles equiponderadas y modelos GARCH. Por consiguiente, la comparación de la precisión de las medidas VaR tiene dos dimensiones: el modelo multifactorial y la medida de volatilidad. Respecto a los modelos multifactoriales, la evidencia presentada indica que el sistema de mapping o cartografía es el modelo más preciso cuando se calculan medidas VaR (5%). Por el contrario, a un nivel de confianza del 1% el modelo paramétrico (modelo de Nelson y Siegel) es el que genera medidas VaR más precisas. Respecto a las medidas de volatilidad los resultados indican que en general no hay una medida que funcione sistemáticamente mejor que el resto en todos los modelos. Salvo alguna excepción, los resultados obtenidos son independientes del horizonte para el cual se calcula el VaR, ya sea uno o diez días.

Suggested Citation

  • Pilar Abad & Sonia Benito, 2006. "Valor en Riesgo en carteras de renta fija: una comparación entre modelos empíricos de la estructura temporal," Documentos de Trabajo del ICAE 0604, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:0604
    as

    Download full text from publisher

    File URL: http://eprints.ucm.es/7912/1/0604.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Chambers, Donald R. & Carleton, Willard T. & McEnally, Richard W., 1988. "Immunizing Default-Free Bond Portfolios with a Duration Vector," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(01), pages 89-104, March.
    2. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    3. Khang, Chulsoon, 1979. "Bond Immunization When Short-Term Interest Rates Fluctuate More Than Long-Term Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 14(05), pages 1085-1090, December.
    4. Bierwag, G. O., 1977. "Immunization, Duration, and the Term Structure of Interest Rates," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(05), pages 725-742, December.
    5. Eliseo Navarro & Juan M. Nave, 2001. "The structure of spot rates and immunization: Some further results," Spanish Economic Review, Springer;Spanish Economic Association, vol. 3(4), pages 273-294.
    6. 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.
    7. Elton, Edwin J & Gruber, Martin J & Michaely, Roni, 1990. " The Structure of Spot Rates and Immunization," Journal of Finance, American Finance Association, vol. 45(2), pages 629-642, June.
    8. Bierwag, G O & Kaufman, George G, 1977. "Coping with the Risk of Interest-Rate Fluctuations: A Note," The Journal of Business, University of Chicago Press, vol. 50(3), pages 364-370, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Value at Risk (VaR); Modelos factoriales; Gestión de riesgo.;

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:ucm:doicae:0604. 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: (Águeda González Abad). General contact details of provider: http://edirc.repec.org/data/feucmes.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.