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.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
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:
Contact details of provider:
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.
Web page: http://www.greqam.fr/
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.:
- Kamstra, M., 1991. "A Neural Network Test for Heteroskedasticity," Discussion Papers dp91-06, Department of Economics, Simon Fraser University.
- 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.
- 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.
- Tom Doan, . "REGRESET: RATS procedure to perform Ramsey RESET test on regression," Statistical Software Components RTS00181, Boston College Department of Economics.
- Tom Doan, . "REGWHITENNTEST: RATS procedure to perform White neural network test on regression," Statistical Software Components RTS00183, Boston College Department of Economics.
- 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.
- 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.
- 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,"
496, Queen Mary, University of London, School of Economics and Finance.
- Blake, Andrew P. & Kapetanios, George, 2007. "Testing for ARCH in the presence of nonlinearity of unknown form in the conditional mean," Journal of Econometrics, Elsevier, vol. 137(2), pages 472-488, April.
- 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.
- n/a, 1999.
"A Radial Basis Function Artificial Neural Network Test for ARCH,"
NIESR Discussion Papers
188, National Institute of Economic and Social Research.
- Blake, Andrew P. & Kapetanios, George, 2000. "A radial basis function artificial neural network test for ARCH," Economics Letters, Elsevier, vol. 69(1), pages 15-23, October.
- 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).
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Krichel).
If references are entirely missing, you can add them using this form.