Wild bootstrap tests for autocorrelation in vector autoregressive models
type: Item
instance of: scholarly article
title: Wild bootstrap tests for autocorrelation in vector autoregressive models
zbMATH Open document ID: 1383.62203
author: Niklas Ahlgren
author: Paul Catani
published in: Statistical Papers
publication date: 2017-12-13T00:00:00Z
full work available at URL: http://hdl.handle.net/10138/36634
review text: The authors consider the problem of testing for the autocorrelation error in VAR models and in vector error correction models. All results are obtained under the assumptions that the errors represent a martingale difference sequence with at least 8th moments, with satisfied convergence of conditional moments and restrictions for the fourth-order cumulants. All tests are based on the Lagrange multiplier statistic. The authors propose wild bootstrap Lagrange multiplier tests for the autocorrelation error and show that these tests are asymptotically valid. Some applications of the proposed tests are discussed on credit default swap prices and Euribor interest rates.
reviewed by: Miroslav M. Ristić
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62G09
Mathematics Subject Classification ID: 62P05
zbMATH DE Number: 6818222
zbMATH Keywords: autocorrelation
zbMATH Keywords: conditional heteroskedasticity
zbMATH Keywords: heteroskedasticity-consistent covariance matrix estimator
zbMATH Keywords: Lagrange multiplier test
zbMATH Keywords: vector autoregressive model
zbMATH Keywords: wild bootstrap
describes a project that uses: R
describes a project that uses: ccgarch
MaRDI profile type: Publication
OpenAlex ID: W2170822754
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DOI: 10.1007/S00362-016-0744-0
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description: scientific article; zbMATH DE number 6818222