Diagnostic Checking in Multivariate ARMA Models With Dependent Errors Using Normalized Residual Autocorrelations
| Autor: | Maïnassara, Yacouba Boubacar, Saussereau, Bruno |
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| Rok vydání: | 2024 |
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| Zdroj: | Journal of the American Statistical Association, 2018, 113 (524), pp.1813-1827 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1080/01621459.2017.1380030 |
| Popis: | In this paper we derive the asymptotic distribution of normalized residual empirical autocovariances and autocorrelations under weak assumptions on the noise. We propose new portmanteau statistics for vector autoregressive moving-average (VARMA) models with uncorrelated but non-independent innovations by using a self-normalization approach. We establish the asymptotic distribution of the proposed statistics. This asymptotic distribution is quite different from the usual chi-squared approximation used under the independent and identically distributed assumption on the noise, or the weighted sum of independent chi-squared random variables obtained under nonindependent innovations. A set of Monte Carlo experiments and an application to the daily returns of the CAC40 is presented. Comment: arXiv admin note: text overlap with arXiv:1902.03000 |
| Databáze: | arXiv |
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