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Shrinkage Regularization for (Non)Linear Serial Dependence Test

Francesco Giancaterini, Alain Hecq, Joann Jasiak, Aryan Manafi Neyazi

arXiv 10 Mar 2026 · Econometrics

arXiv:2603.10152 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper introduces a regularized test of the null hypothesis of the absence of linear and nonlinear serial dependence for high-dimensional non-Gaussian time series. Our approach extends the portmanteau test introduced in Jasiak and Neyazi (2023) to the high-dimensional setting.

Citation extraction

9
references
25
in-text mentions
9
distinct cited
4
self-citations
2,495
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Ledoit, Olivier and Wolf, Michael (2004) A well-conditioned estimator for large-dimensional covariance matrices1.000113100%
2Giancaterini, Francesco and Hecq, Alain and Jasiak, Joann and Neyazi… (2025) Regularized generalized covariance (rgcov) estimator self0.81142100%
3Jasiak, Joann and Neyazi, Aryan M (2023) GCov-Based Portmanteau Test self0.73732100%
4Gourieroux, Christian and Jasiak, Joann (2023) Generalized covariance estimator self0.51121100%
5Chan, Kung-Sik and Ho, Lop-Hing and Tong, Howell (2006) A note on time-reversibility of multivariate linear processes0.40511100%
6Chitturi, Ratnam V (1976) Distribution of multivariate white noise autocorrelations0.40511100%
7Escanciano, J Carlos and Lobato, Ignacio N (2009) An automatic portmanteau test for serial correlation0.40511100%
8Gourieroux, Christian and Jasiak, Joann (2017) Noncausal vector autoregressive process: Representation, identification and semi-parametric estimation self0.40511100%
9Pourahmadi, Mohsen (2013) High-dimensional covariance estimation: with high-dimensional data0.40511100%

Showing the top 9 of 9 scored citations.