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

IF 3.8 3区经济学 Q1 BUSINESS, FINANCE

North American Journal of Economics and Finance Pub Date : 2025-01-01 DOI:10.1016/j.najef.2025.102381

Cuixia Jiang , Junwei Sun , Qifa Xu

引用次数: 0

Abstract

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.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

North American Journal of Economics and Finance Multiple-

CiteScore

7.30

自引率

8.30%

发文量

168

期刊介绍： The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.