Risk Ranking from Financial Reports

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题名:	Risk Ranking from Financial Reports
作者:	Tsai, Ming-Feng;Wang, Chuan-Ju;王釧茹
贡献者:	臺北市立教育大學資訊科學系
关键词:	Ranking;Soft Information;Volatility;Financial Report
日期:	2013
上传时间:	2019-02-14
摘要:	This paper attempts to use soft information in finance to rank the risk levels of a set of companies. Specifically, we deal with a ranking problem with a collection of financial reports, in which each report is associated with a company. By using text information in the reports, which is so-called the soft information, we apply learning-to-rank techniques to rank a set of companies to keep them in line with their relative risk levels. In our experiments, a collection of financial reports, which are annually published by publicly-traded companies, is employed to evaluate our ranking approach; moreover, a regression-based approach is also carried out for comparison. The experimental results show that our ranking approach not only significantly outperforms the regression-based one, but identifies some interesting relations between financial terms.
關聯:	the 35th annual European Conference on Information Retrieval (ECIR’13)，Moscow，2013
显示于类别:	[資訊科學系] 會議論文

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