财务困境
业务
投资(军事)
精算学
实证研究
特征(语言学)
苦恼
财务
会计
心理学
政治学
金融体系
认识论
哲学
政治
语言学
法学
心理治疗师
作者
Cuiqing Jiang,Yiru Zhou,Bo Chen
标识
DOI:10.1016/j.techfore.2023.122450
摘要
Financial distress prediction has been a popular topic over the decades. Most studies have used accounting features from financial statements to predict financial distress. Compared to listed companies, unlisted public companies have longer financial disclosure cycles, less required disclosure of market trading information, and higher financial risk. However, they can also have a strong ability to innovate and great growth potential, attributes that cannot be fully reflected in financial statements. In this study, as a supplement to accounting features, we propose a framework for mining the statistical features and semantic features in patent text by comprehensively analyzing the patent's structured information, abstract, claims, citations, and specifications. The results of empirical evaluation confirm that patent features contain incremental information related to financial distress. This research broadens the feature space of financial distress research and expands the research on patent text. It also provides decision support for banks approving loans, investment decision-making, and patent pledges.
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