A Comparison of the Power of Some Tests for Conditional Heteroscedasticity
AbstractThis 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 InfoPaper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 99a22.
Length: 13 pages
Date of creation: 1999
Date of revision:
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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.
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More information through EDIRC
TESTING ; ECONOMETRICS ; HETEROSKEDASTICITY;
Other versions of this item:
- Peguin-Feissolle, Anne, 1999. "A comparison of the power of some tests for conditional heteroscedasticity," Economics Letters, Elsevier, vol. 63(1), pages 5-17, April.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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.:
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- 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.
- 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.
- 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.
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