Two-way Matrix Autoregressive Model with Thresholds

Fuente: arXiv
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Autori principali: Yu, Cheng, Li, Dong, Zhang, Xinyu, Tong, Howell
Natura: Preprint
Pubblicazione: 2024
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author Yu, Cheng
Li, Dong
Zhang, Xinyu
Tong, Howell
author_facet Yu, Cheng
Li, Dong
Zhang, Xinyu
Tong, Howell
contents Recently, matrix-valued time series data have attracted significant attention in the literature with the recognition of threshold nonlinearity representing a significant advance. However, given the fact that a matrix is a two-array structure, it is unfortunate, perhaps even unusual, for the threshold literature to focus on using the same threshold variable for the rows and the columns. In fact, evidence in economic, financial, environmental and other data shows advantages of allowing the possibilities of two different threshold variables (with possibly different threshold parameters for rows and columns), hence the need for a Two-way Matrix AutoRegressive model with Thresholds (2-MART). Naturally, two threshold variables pose new and perhaps even fierce challenges, which might be the reason behind the adoption of only one threshold variable in the literature up to now. In this paper, we develop a comprehensive methodology for the 2-MART model, by overcoming various challenges. Compared with existing models in the literature, the new model can achieve greater dimension reduction, much better model fitting, more accurate predictions, and more plausible interpretations.
format Preprint
id arxiv_https___arxiv_org_abs_2407_10272
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Two-way Matrix Autoregressive Model with Thresholds
Yu, Cheng
Li, Dong
Zhang, Xinyu
Tong, Howell
Methodology
Recently, matrix-valued time series data have attracted significant attention in the literature with the recognition of threshold nonlinearity representing a significant advance. However, given the fact that a matrix is a two-array structure, it is unfortunate, perhaps even unusual, for the threshold literature to focus on using the same threshold variable for the rows and the columns. In fact, evidence in economic, financial, environmental and other data shows advantages of allowing the possibilities of two different threshold variables (with possibly different threshold parameters for rows and columns), hence the need for a Two-way Matrix AutoRegressive model with Thresholds (2-MART). Naturally, two threshold variables pose new and perhaps even fierce challenges, which might be the reason behind the adoption of only one threshold variable in the literature up to now. In this paper, we develop a comprehensive methodology for the 2-MART model, by overcoming various challenges. Compared with existing models in the literature, the new model can achieve greater dimension reduction, much better model fitting, more accurate predictions, and more plausible interpretations.
title Two-way Matrix Autoregressive Model with Thresholds
topic Methodology
url https://arxiv.org/abs/2407.10272