Financial Sentiment Analysis for Risk Prediction

Title	Financial Sentiment Analysis for Risk Prediction
Creator	Wang, Chuan-Ju;Tsai, Ming-Feng;Liu, Tse;Chang, Chin-Ting 蔡銘峰
Contributor	資科系
Date	2013-10
Date Issued	22-Jun-2016 17:10:38 (UTC+8)
Summary	This paper attempts to identify the importance of sentiment words in financial reports on financial risk. By using a financespecific sentiment lexicon, we apply regression and ranking techniques to analyze the relations between sentiment words and financial risk. The experimental results show that, based on the bag-of-words model, models trained on sentiment words only result in comparable performance to those on origin texts, which confirms the importance of financial sentiment words on risk prediction. Furthermore, the learned models suggest strong correlations between financial sentiment words and risk of companies. As a result, these findings are of great value for providing us more insight and understanding into the impact of financial sentiment words in financial reports.
Relation	Proceedings of the 6th International Joint Conference on Natural Language Processing (IJCNLP `13), 802-808, 2013
Type	conference

dc.contributor	資科系
dc.creator (作者)	Wang, Chuan-Ju;Tsai, Ming-Feng;Liu, Tse;Chang, Chin-Ting
dc.creator (作者)	蔡銘峰	zh_TW
dc.date (日期)	2013-10
dc.date.accessioned	22-Jun-2016 17:10:38 (UTC+8)	-
dc.date.available	22-Jun-2016 17:10:38 (UTC+8)	-
dc.date.issued (上傳時間)	22-Jun-2016 17:10:38 (UTC+8)	-
dc.identifier.uri (URI)	http://nccur.lib.nccu.edu.tw/handle/140.119/98232	-
dc.description.abstract (摘要)	This paper attempts to identify the importance of sentiment words in financial reports on financial risk. By using a financespecific sentiment lexicon, we apply regression and ranking techniques to analyze the relations between sentiment words and financial risk. The experimental results show that, based on the bag-of-words model, models trained on sentiment words only result in comparable performance to those on origin texts, which confirms the importance of financial sentiment words on risk prediction. Furthermore, the learned models suggest strong correlations between financial sentiment words and risk of companies. As a result, these findings are of great value for providing us more insight and understanding into the impact of financial sentiment words in financial reports.
dc.format.extent	800435 bytes	-
dc.format.mimetype	application/pdf	-
dc.relation (關聯)	Proceedings of the 6th International Joint Conference on Natural Language Processing (IJCNLP `13), 802-808, 2013
dc.title (題名)	Financial Sentiment Analysis for Risk Prediction
dc.type (資料類型)	conference