Normality test for multivariate conditional heteroskedastic dynamic regression models

DOI10.1016/j.econlet.2011.01.015zbMath1211.62154OpenAlexW2044046323MaRDI QIDQ533940

Chi Tim Ng, Sangyeol Lee

Publication date: 10 May 2011

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

Full work available at URL: https://doi.org/10.1016/j.econlet.2011.01.015

zbMATH Keywords

distribution free testJarque-Bera testmultivariate GARCH modelsnormality test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Hypothesis testing in multivariate analysis (62H15)

Related Items (1)

Tests for multivariate normality -- a critical review with emphasis on weighted $L^2$-statistics

Cites Work

• Unnamed Item
• Testing multivariate distributions in GARCH models
• Asymptotic normality of the quasi-maximum likelihood estimator for multidimensional causal processes
• Asymptotic theory for multivariate GARCH processes.
• The efficiency of the estimators of the parameters in GARCH processes.
• On the validity of the Jarque-Bera normality test in conditionally heteroskedastic dynamic regression models
• On some global measures of the deviations of density function estimates
• High moment partial sum processes of residuals in GARCH models and their applications
• A note on the Jarque-Bera normality test for GARCH innovations
• Multivariate skewt-distribution
• An Appraisal and Bibliography of Tests for Multivariate Normality

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