High-Dimensional Cointegration and Kuramoto Inspired Systems

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Main Authors: Stærk-Østergaard, Jacob, Rahbek, Anders, Ditlevsen, Susanne
Format: Recurso digital
Language:English
Published: Zenodo 2024
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author Stærk-Østergaard, Jacob
Rahbek, Anders
Ditlevsen, Susanne
author_facet Stærk-Østergaard, Jacob
Rahbek, Anders
Ditlevsen, Susanne
contents <p>This paper presents a novel estimator for a nonstandard restriction to both symmetry and low rank in the context of high-dimensional cointegrated processes. Furthermore, we discuss rank estimation for high-dimensional cointegrated processes by restricted bootstrapping of the Gaussian innovations. We demonstrate that the classical <em>rank test</em> for cointegrated systems is prone to underestimating the true rank and demonstrate this effect in a 100-dimensional system. We also discuss the implications of this underestimation for such high-dimensional systems in general. Also, we define a linearized Kuramoto system and present a simulation study, where we infer the cointegration rank of the unrestricted system and successively the underlying clustered network structure based on a graphical approach and a symmetrized low rank estimator of the couplings derived from a reparametrization of the likelihood under this unusual restriction.</p>
format Recurso digital
id zenodo_https___doi_org_10_1137_22M1509771
institution Zenodo
language eng
publishDate 2024
publisher Zenodo
record_format zenodo
spellingShingle High-Dimensional Cointegration and Kuramoto Inspired Systems
Stærk-Østergaard, Jacob
Rahbek, Anders
Ditlevsen, Susanne
<p>This paper presents a novel estimator for a nonstandard restriction to both symmetry and low rank in the context of high-dimensional cointegrated processes. Furthermore, we discuss rank estimation for high-dimensional cointegrated processes by restricted bootstrapping of the Gaussian innovations. We demonstrate that the classical <em>rank test</em> for cointegrated systems is prone to underestimating the true rank and demonstrate this effect in a 100-dimensional system. We also discuss the implications of this underestimation for such high-dimensional systems in general. Also, we define a linearized Kuramoto system and present a simulation study, where we infer the cointegration rank of the unrestricted system and successively the underlying clustered network structure based on a graphical approach and a symmetrized low rank estimator of the couplings derived from a reparametrization of the likelihood under this unusual restriction.</p>
title High-Dimensional Cointegration and Kuramoto Inspired Systems
url https://doi.org/10.1137/22M1509771