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題名 On the risk prediction and analysis of soft information in finance reports
作者 Tsai, Ming-Feng;Wang, Chuan-Ju
蔡銘峰
貢獻者 資科系
關鍵詞 Finance; Risk prediction; Text mining; Sentiment analysis
日期 2017-02
上傳時間 15-十二月-2016 16:17:40 (UTC+8)
摘要 We attempt in this paper to utilize soft information in financial reports to analyze financial risk among companies. Specifically, on the basis of the text information in financial reports, which is the so-called soft information, we apply analytical techniques to study relations between texts and financial risk. Furthermore, we conduct a study on financial sentiment analysis by using a finance-specific sentiment lexicon to examine the relations between financial sentiment words and financial risk. A large collection of financial reports published annually by publicly-traded companies is employed to conduct our experiments; moreover, two analytical techniques – regression and ranking methods – are applied to conduct these analyses. The experimental results show that, based on a bag-of-words model, using only financial sentiment words results in performance comparable to using the whole texts; this confirms the importance of financial sentiment words with respect to risk prediction. In addition to this performance comparison, via the learned models, we draw attention to some strong and interesting correlations between texts and financial risk. These valuable findings yield greater insight and understanding into the usefulness of soft information in financial reports and can be applied to a broad range of financial and accounting applications.
關聯 European Journal of Operational Research, Volume 257, Issue 1, Pages 243–250
資料類型 article
DOI http://dx.doi.org/10.1016/j.ejor.2016.06.069
dc.contributor 資科系
dc.creator (作者) Tsai, Ming-Feng;Wang, Chuan-Ju
dc.creator (作者) 蔡銘峰zh_TW
dc.date (日期) 2017-02
dc.date.accessioned 15-十二月-2016 16:17:40 (UTC+8)-
dc.date.available 15-十二月-2016 16:17:40 (UTC+8)-
dc.date.issued (上傳時間) 15-十二月-2016 16:17:40 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/104953-
dc.description.abstract (摘要) We attempt in this paper to utilize soft information in financial reports to analyze financial risk among companies. Specifically, on the basis of the text information in financial reports, which is the so-called soft information, we apply analytical techniques to study relations between texts and financial risk. Furthermore, we conduct a study on financial sentiment analysis by using a finance-specific sentiment lexicon to examine the relations between financial sentiment words and financial risk. A large collection of financial reports published annually by publicly-traded companies is employed to conduct our experiments; moreover, two analytical techniques – regression and ranking methods – are applied to conduct these analyses. The experimental results show that, based on a bag-of-words model, using only financial sentiment words results in performance comparable to using the whole texts; this confirms the importance of financial sentiment words with respect to risk prediction. In addition to this performance comparison, via the learned models, we draw attention to some strong and interesting correlations between texts and financial risk. These valuable findings yield greater insight and understanding into the usefulness of soft information in financial reports and can be applied to a broad range of financial and accounting applications.
dc.format.extent 1183523 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) European Journal of Operational Research, Volume 257, Issue 1, Pages 243–250
dc.subject (關鍵詞) Finance; Risk prediction; Text mining; Sentiment analysis
dc.title (題名) On the risk prediction and analysis of soft information in finance reports
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/j.ejor.2016.06.069
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.ejor.2016.06.069