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Estimating and forecasting structural breaks in financial time series

  • BAUWENS, Luc

    ()

    (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium)

  • DUFAYS, Arnaud

    ()

    (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium)

  • DE BACKER, Bruno

We present an algorithm, based on a differential evolution MCMC method, for Bayesian inference in AR-GARCH models subject to an unknown number of structural breaks at unknown dates. Break dates are directly treated as parameters and the number of breaks is determined by the marginal likelihood criterion. We prove the convergence of the algorithm and we show how to compute marginal likelihoods. We allow for both pure change-point and recurrent regime specifications and we show how to forecast structural breaks. We illustrate the efficiency of the algorithm through simulations and we apply it to eight financial time series of daily returns over the period 1987-2011. We find at least three breaks in all series.

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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2011055.

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Date of creation: 21 Nov 2011
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Handle: RePEc:cor:louvco:2011055
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  1. Luc Bauwens & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-Switching and Change-Point GARCH Models," Cahiers de recherche 1138, CIRPEE.
  2. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  3. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  4. repec:cup:cbooks:9780521681599 is not listed on IDEAS
  5. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 211-250.
  6. Pesaran, M. Hashem & Pettenuzzo, Davide & Timmermann, Allan, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," IZA Discussion Papers 1196, Institute for the Study of Labor (IZA).
  7. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
  8. Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, School of Economics and Management, University of Aarhus.
  9. repec:cup:cbooks:9780521715348 is not listed on IDEAS
  10. repec:cup:cbooks:9780521887427 is not listed on IDEAS
  11. repec:bla:restud:v:73:y:2006:i:4:p:1057-1084 is not listed on IDEAS
  12. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
  13. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
  14. Duranton, Gilles & Martin, Philippe & Mayer, Thierry & Mayneris, Florian, 2010. "The Economics of Clusters: Lessons from the French Experience," OUP Catalogue, Oxford University Press, number 9780199592203, March.
  15. Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2008. "AdMit: Adaptive Mixtures of Student-t Distributions," DQE Working Papers 10, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 07 Jan 2009.
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