Risk Ranking from Financial Reports

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Title:	Risk Ranking from Financial Reports
Authors:	王釧茹蔡銘峰
Contributors:	台北市立大學國立政治大學
Keywords:	Ranking Soft Information Volatility Financial Report
Date:	2013
Issue Date:	2013-08-06 11:37:44 (UTC+8)
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.
Appears in Collections:	[Department of Computer Science] Research Project

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