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Improved multivariate portmanteau test
Authors:Esam Mahdi  A. Ian McLeod
Affiliation:The University of Western Ontario
Abstract:A new portmanteau diagnostic test for vector autoregressive moving average (VARMA) models that is based on the determinant of the standardized multivariate residual autocorrelations is derived. The new test statistic may be considered an extension of the univariate portmanteau test statistic suggested by Peňa and Rodríguez (2002) . The asymptotic distribution of the test statistic is derived as well as a chi‐square approximation. However, the Monte–Carlo test is recommended unless the series is very long. Extensive simulation experiments demonstrate the usefulness of this test as well as its improved power performance compared to widely used previous multivariate portmanteau diagnostic check. Two illustrative applications are given.
Keywords:Diagnostic checking  multivariate time series  parallel computing  Monte Carlo significance test  residual autocorrelation function  VARMA models
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