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Volatility bias in the GARCH model: a simulation study

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Author Info
Eduardo Acosta González ()
Fernando Fernández Rodríguez ()
Jorge Pérez Rodríguez ()
Abstract

In this paper we show that the conditional variance of the GARCH(1,1) model is a measure that usually overstimates the magnitude of volatility in time series.

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Publisher Info
Paper provided by Facultad de Ciencias Económicas de la ULPGC in its series Documentos de trabajo conjunto ULL-ULPGC with number 2002-02.

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Length: 11 pages
Date of creation: 2002
Date of revision:
Handle: RePEc:can:series:2002-02

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Keywords: GARCH models; prediction; bias;

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Tim Bollerslev & Jeffrey Wooldridge, 1992. "Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances," Econometric Reviews, Taylor and Francis Journals, vol. 11(2), pages 143-172. [Downloadable!] (restricted)
  2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  3. Engle, Robert F & Gonzalez-Rivera, Gloria, 1991. "Semiparametric ARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 345-59, October.
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  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July. [Downloadable!] (restricted)
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