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A Comparison of the Power of Some Tests for Conditional Heteroscedasticity

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  • Peguin-Feissolle, A.

Abstract

This paper compares the power in small samples of different tests for conditional heteroscedasticity. Two new tests, based on neural networks, are proposed: the main interest in them arises from the fact that they do not require the exact specification of the conditional variance under the alternative.

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Bibliographic Info

Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 99a22.

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Length: 13 pages
Date of creation: 1999
Date of revision:
Handle: RePEc:fth:aixmeq:99a22

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Postal: G.R.E.Q.A.M., (GROUPE DE RECHERCHE EN ECONOMIE QUANTITATIVE D'AIX MARSEILLE), CENTRE DE VIEILLE CHARITE, 2 RUE DE LA CHARITE, 13002 MARSEILLE.
Phone: 04.91.14.07.70
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Web page: http://www.greqam.fr/
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Related research

Keywords: TESTING ; ECONOMETRICS ; HETEROSKEDASTICITY;

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References

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  1. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
  2. Bera, Anil K & Higgins, Matthew L, 1993. " ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-66, December.
  3. Kamstra, M., 1991. "A Neural Network Test for Heteroskedasticity," Discussion Papers dp91-06, Department of Economics, Simon Fraser University.
  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.
  5. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
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Cited by:
  1. n/a, 1999. "A Radial Basis Function Artificial Neural Network Test for ARCH," NIESR Discussion Papers 188, National Institute of Economic and Social Research.
  2. Teresa Aparicio & Inmaculada Villanua, 2001. "The asymptotically efficient version of the information matrix test in binary choice models. A study of size and power," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(2), pages 167-182.
  3. Andrew P. Blake & George Kapetanios, 2003. "Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean," Working Papers 496, Queen Mary, University of London, School of Economics and Finance.
  4. Burkhard Raunig, 2003. "Testing for Longer Horizon Predictability of Return Volatility with an Application to the German," Working Papers 86, Oesterreichische Nationalbank (Austrian Central Bank).
  5. Gilles Dufrénot & Vêlayoudom Marimoutou & Anne Péguin-Feissolle, 2004. "Modeling the volatility of the US SαP 500 index using an LSTGARCH model," Revue d'économie politique, Dalloz, vol. 0(4), pages 453-465.

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