A note on Portmanteau tests for conditional heteroscedastistic models

Ben, Youhong; Jiang, Feiyu

doi:10.1016/j.econlet.2020.109159

Cited by 1 publication

(2 citation statements)

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“…(2021) when the power

{\underline{δ}}_{0}

is unknown and is jointly estimated with the other parameters. See also Ben and Jiang (2020) who recently extended the work of Carbon and Francq (2011) (when

{\underline{δ}}_{0}

is known and when some parameters lie on the boundary) to the class of APGARCH with exogenous covariates (APGARCH‐X). In the multi‐variate analysis, there are a few works.…”

Section: Introductionmentioning

confidence: 99%

“…For the univariate APGARCH model, a portmanteau test based on the autocovariances of the squared residuals is developed by Carbon and Francq (2011) for the APGARCH model when the power 𝛿 0 is known and by Boubacar Maïnassara et al (2021) when the power 𝛿 0 is unknown and is jointly estimated with the other parameters. See also Ben and Jiang (2020) who recently extended the work of Carbon and Francq (2011) (when 𝛿 0 is known and when some parameters lie on the boundary) to the class of APGARCH with exogenous covariates (APGARCH-X). In the multi-variate analysis, there are a few works.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Portmanteau test for a class of multivariate asymmetric power GARCH model

Maïnassara

Kadmiri

Saussereau

2022

Journal Time Series Analysis

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We establish the asymptotic behaviour of the sum of squared residuals autocovariances and autocorrelations for the class of multi-variate power transformed asymmetric models. We then derive a portmanteau test. We establish the asymptotic distribution of the proposed statistics. These asymptotic results are illustrated by Monte Carlo experiments. An application to a bivariate real financial data is also proposed.

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“…(2021) when the power

{\underline{δ}}_{0}

is unknown and is jointly estimated with the other parameters. See also Ben and Jiang (2020) who recently extended the work of Carbon and Francq (2011) (when

{\underline{δ}}_{0}

is known and when some parameters lie on the boundary) to the class of APGARCH with exogenous covariates (APGARCH‐X). In the multi‐variate analysis, there are a few works.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%