Risk Ranking from Financial Reports

uTaipei > College of Science > Department of Computer Science > Proceedings > Item 987654321/16978

Please use this identifier to cite or link to this item: http://utaipeir.lib.utaipei.edu.tw/dspace/handle/987654321/16978

Title:	Risk Ranking from Financial Reports
Authors:	Tsai, Ming-Feng;Wang, Chuan-Ju;王釧茹
Contributors:	臺北市立教育大學資訊科學系
Keywords:	Ranking;Soft Information;Volatility;Financial Report
Date:	2013
Issue Date:	2019-02-14
Abstract:	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.
Relation:	the 35th annual European Conference on Information Retrieval (ECIR’13)，Moscow，2013
Appears in Collections:	[Department of Computer Science] Proceedings

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