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Indice de turbulencia financiera para Argentina mediante un modelo SWARCH

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  • Emiliano Delfau

Abstract

El objetivo del presente trabajo es desarrollar un índice de turbulencia argentino mediante la estimación de un modelo GARCH con proceso Markov (SWARCH). Estos modelos se han vuelto populares dado que permiten explicar cambios de regímenes en la varianza condicional de una serie de tiempo. En nuestro caso particular utilizaremos la tasa Badlar como serie de tiempo a modo de poder obtener dos momentos o regímenes de volatilidad uno denominado “calmo” o de baja volatilidad y otro denominado “turbulencia” o de alta volatilidad.

Suggested Citation

  • Emiliano Delfau, 2018. "Indice de turbulencia financiera para Argentina mediante un modelo SWARCH," CEMA Working Papers: Serie Documentos de Trabajo. 656, Universidad del CEMA.
    • Handle: RePEc:cem:doctra:656
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    References listed on IDEAS

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    1. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    4. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 211-250.
    5. David Ardia, 2008. "Financial Risk Management with Bayesian Estimation of GARCH Models," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-78657-3, October.
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