基于财务报表衡量公司相似性的比较研究

Zhiwen Zhang
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引用次数: 0

摘要

对于金融研究人员来说,衡量公司之间的相似性非常重要。本段根据研究对象和研究方法对该领域的参考文献进行了分类。具体来说,根据数据结构和数据连接性可分为四种研究对象。研究方法也可根据数据形式和建模类型分为四种。可以得出的结论是,基于图论的模型存在学术空白:无论是独立数据还是非结构化数据,都应得到更广泛的应用。此外,在预测模型中引入向量时,应更多地使用相互关联的结构化数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comparative Study on Measuring Similarity between Companies Based on Financial Statements
It is important for financial researchers to measure similarity between companies. This passage classifies references in this area based on research objects and research methods. To be more specific, there are four research objects based on data structure and data connectivity. Research methods can also be classified into four types based on data form and modeling type. It can be concluded that there are academic blanks on models based on graph theory: no matter independent data or unstructured data should be used more wildly. Moreover, interconnected structured data should be used more often when vectors are introduced into predictive modeling.
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