A penalized U-MIDAS multinomial logit model with applications to corporate credit ratings

作     者：Jiang, Cuixia Sun, Junwei Xu, Qifa 

作者机构：Hefei Univ Technol Sch Management Hefei 230009 Anhui Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei 230009 Anhui Peoples R China Tunxi Rd 193 Hefei Anhui Peoples R China 

出 版 物：《NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE》 (North Am. J. Econ. Financ.)

年 卷 期：2025年第76卷

核心收录：

学科分类：02[经济学] 1202[管理学-工商管理] 0201[经济学-理论经济学] 

基　　金：National Natural Science Foundation of China National Social Science Foundation of China [21BJY255] 

主　　题：Corporate credit ratings U-MIDAS regression Multinomial logit model Group LASSO 

摘      要：We develop a penalized U-MIDAS-Mlogit model by introducing the group LASSO penalty into the unrestricted MIDAS multinomial logit model. This penalized U-MIDAS-Mlogit model can implement multinomial classification in a high-dimensional mixed-frequency data environment. We apply it to credit ratings for listed companies in China over the period 2008-2023. The penalized U-MIDAS-Mlogit model can extract pivotal information from high-frequency financial variables and low-frequency internal and external governance indicators. It outperforms several competing models in predicting credit ratings.