Identification of matrix-valued factor models

被引：0
|
作者：
Cheung, Ying Lun [1 ]
机构：
[1] Capital Univ Econ & Business, Beijing, Peoples R China
来源：
ECONOMICS BULLETIN | 2024年 / 44卷 / 02期
基金：
中国国家自然科学基金;
关键词：
PRINCIPAL COMPONENTS; NUMBER; ARBITRAGE; MOMENTUM;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
The analysis of matrix-valued time series has been popular in recent years. When the dimensions of the matrix observations are large, one can use the matrix-valued factor model to extract information from the data. However, as in standard factor analysis, the common factors and factor loadings are not separately identifiable. This note considers two sets of identification restrictions that help exactly identify the model.
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页数：8
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