A comparison of the power of some tests for conditional heteroscedasticity

DOI10.1016/S0165-1765(99)00010-5zbMath0916.90049WikidataQ126527828 ScholiaQ126527828MaRDI QIDQ1285811

Anne Peguin-Feissolle

Publication date: 28 April 1999

Published in: Economics Letters (Search for Journal in Brave)

zbMATH Keywords

hypothesis testingartificial neural networksconditional heteroscedasticity

Mathematics Subject Classification ID

Statistical methods; economic indices and measures (91B82)

Related Items (6)

Testing for ARCH in the presence of nonlinearity of unknown form in the conditional mean ⋮ The asymptotically efficient version of the information matrix test in binary choice models. A study of size and power ⋮ Analysing the performance of bootstrap neural tests for conditional heteroskedasticity in ARCH-M models ⋮ A radial basis function artificial neural network test for neglected nonlinearity ⋮ A radial basis function artificial neural network test for ARCH ⋮ Robust Lagrange multiplier test for detecting ARCH/GARCH effect using permutation and bootstrap

Cites Work

• Unnamed Item
• ARCH modeling in finance. A review of the theory and empirical evidence
• Testing for neglected nonlinearity in time series models. A comparison of neural network methods and alternative tests
• Multilayer feedforward networks are universal approximators
• DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED-RESIDUAL AUTOCORRELATIONS
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

This page was built for publication: A comparison of the power of some tests for conditional heteroscedasticity