Falsifying ARCH/GARCH Models Using Bispectral Based Tests

DOI10.1080/03610920802245741zbMath1159.62057OpenAlexW2019750807MaRDI QIDQ3622068

Melvin J. Hinich

Publication date: 23 April 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802245741

zbMATH Keywords

reversibilitytrimmingbispectrum

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Non-Markovian processes: hypothesis testing (62M07)

Related Items (1)

Long-range dependence in third order and bispectrum singularity

Cites Work

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• Bootstrapping the Box-Pierce \(Q\) test: a robust test of uncorrelatedness
• ARCH modeling in finance. A review of the theory and empirical evidence
• Using discrete-time techniques to test continuous-time models for nonlinearity in drift
• Normalizing bispectra
• Generalized autoregressive conditional heteroscedasticity
• Bispectral-Based Tests for the Detection of Gaussianity and Linearity in Time Series
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• TESTING FOR GAUSSIANITY AND LINEARITY OF A STATIONARY TIME SERIES
• A NEW DIAGNOSTIC TEST OF MODEL INADEQUACY WHICH USES THE MARTINGALE DIFFERENCE CRITERION
• An Introduction to Polyspectra

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