A novel semisupervised learning method with textual information for financial distress prediction

Author:

Qiu Yue1,He Jiabei1,Chen Zhensong1ORCID,Yao Yinhong1,Qu Yi2ORCID

Affiliation:

1. School of Management and Engineering Capital University of Economics and Business Beijing China

2. School of Economics and Management University of Chinese Academy of Sciences Beijing China

Abstract

AbstractFinancial distress prediction (FDP) has attracted high attention from many financial institutions. Utilizing supervised learning‐based methods in FDP, however, is time consuming and labor intensive. Therefore, in this paper, we exploit active‐pSVM method, which combines potential data distribution information and existing expert experience to solve FDP problem. Moreover, with the increasingly popular textual information, we construct several features on our protocol that are based on the Management Discussion and Analysis (MD&A) text information. Using datasets that are collected in different time windows from the listed Chinese companies, we conducted an extensive experiment and were able to confirm a better efficiency of our active‐pSVM, when compared with some common supervised learning‐based methods. Our study also covers the application of MD&A text information on weakly supervised learning model in FDP.

Funder

National Natural Science Foundation of China

Beijing Municipal Commission of Education

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3