English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 92416/122720 (75%)
Visitors : 26257165      Online Users : 134
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/104953
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/104953


    Title: On the risk prediction and analysis of soft information in finance reports
    Authors: Tsai, Ming-Feng;Wang, Chuan-Ju
    蔡銘峰
    Contributors: 資科系
    Keywords: Finance;Risk prediction;Text mining;Sentiment analysis
    Date: 2017-02
    Issue Date: 2016-12-15 16:17:40 (UTC+8)
    Abstract: 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.
    Relation: European Journal of Operational Research, Volume 257, Issue 1, Pages 243–250
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.ejor.2016.06.069
    DOI: 10.1016/j.ejor.2016.06.069
    Appears in Collections:[資訊科學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    243-250.pdf1155KbAdobe PDF383View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback