caa a22 4500 378906836 CHVBK 20180305123531.0 cr unu---uuuuu 161128e20040916xx s 000 0 eng 10.2202/1558-3708.1239 doi (NATIONALLICENCE)gruyter-10.2202/1558-3708.1239 Neural Tests for Conditional Heteroskedasticity in ARCH-M Models [Elektronische Daten] [Christian de Peretti, Carole Siani] This paper deals with tests for detecting conditional heteroskedasticity in ARCH-M models using three kinds of methods: neural networks techniques, bootstrap methods and both combined.As regards the ARCH models, Péguin-Feissolle (2000) developed tests based on the modelling techniques with neural network. However, as regards the ARCH-M models, a nuisance parameter is not identified and the tests are not applicable. To solve this problem, we propose to adapt these neural tests to Davies procedure (1987) leading to new tests. The performance of these latter tests are compared with those of Bera and Ra test (1995).However, Bera and Ra test has not really satisfactory performance and suffer from serious size distortion. Our neural test will have the same problem. To solve this second problem, without loss of power, we apply parametric and nonparametric bootstrap methods on the underlying test statistics.Lastly, to examine the size and the power properties of the tests in small samples, Monte Carlo simulations are carried out with various standard and non-standard models for conditional heteroskedasticity as to illustrate a variety of situations. In addition, the graphical presentation of Davidson and MacKinnon (1998a) is used to show the "true" power of the tests and not only the (nominal) power, as it is often the case, that can be meaningless. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston de Peretti Christian GREQAM - University of Aix Marseille II, CREUSET - University of Saint Etienne, peretti@ehess.univ-mrs.fr aut Siani Carole GREQAM - University of Aix Marseille II aut Studies in Nonlinear Dynamics & Econometrics De Gruyter 8/3(2004-09-16) 8:3 2004 8 snde https://doi.org/10.2202/1558-3708.1239 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1558-3708.1239 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- de Peretti Christian GREQAM - University of Aix Marseille II, CREUSET - University of Saint Etienne, peretti@ehess.univ-mrs.fr aut NATIONALLICENCE 700 1- Siani Carole GREQAM - University of Aix Marseille II aut NATIONALLICENCE 773 0- Studies in Nonlinear Dynamics & Econometrics De Gruyter 8/3(2004-09-16) 8:3 2004 8 snde CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter