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Evaluating GARCH Models

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Author Info
Stefan Lundbergh (Stockholm School of Economics)
Timo Teräsvirta () (Stockholm School of Economics)

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Abstract

This paper suggests a unified framework for testing the adequacy of an estimated GARCH model. Nothing more complicated than standard asymptotic theory is required. Parametric tests of no ARCH in standardized errors, symmetry, and parameter constancy are suggested. Estimating the alternative when the null hypothesis is rejected may give useful ideas of how to improve the specification. It is also shown that the recent portmanteau test of Li and Mak (1994) is asymptotically equivalent to our test of no ARCH in the standardized error process.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 99-008/4.

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Date of creation: 18 Feb 1999
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Handle: RePEc:dgr:uvatin:19990008

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  1. Fiorentini, Gabriele & Calzolari, Giorgio & Panattoni, Lorenzo, 1996. "Analytic Derivatives and the Computation of GARCH Estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 399-417, July-Aug.. [Downloadable!] (restricted)
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  2. Sentana, Enrique, 1995. "Quadratic ARCH Models," Review of Economic Studies, Blackwell Publishing, vol. 62(4), pages 639-61, October. [Downloadable!] (restricted)
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  3. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December. [Downloadable!] (restricted)
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  4. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March. [Downloadable!] (restricted)
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  5. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September. [Downloadable!] (restricted)
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  6. 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)
  7. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-35, April.
  8. Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Modelling economic high-frequency time series with STAR-STGARCH models," Working Paper Series in Economics and Finance 291, Stockholm School of Economics. [Downloadable!]
  9. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June. [Downloadable!] (restricted)
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  10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  11. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December. [Downloadable!] (restricted)
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  12. 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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