Learning value-added information of asset management from analyst reports through text mining
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Analysis of the effect of Headline News in financial market through text categorisation
International Journal of Computer Applications in Technology
Stock price movement prediction using representative prototypes of financial reports
ACM Transactions on Management Information Systems (TMIS)
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In finance task domain, it is indispensable to get and analyze information as quickly as possible. Analyst’s reports are one of the important information in asset management, and these include a large amount of text information. However, it is very difficult to handle text information of analyst’s reports, few research and development have been conducted. In [5] and [6] we explored the feasibility to extract valuable knowledge for asset management through text mining using analyst’s reports as text data. And we found the effectiveness of keyword information. In this paper we make further research of analyst’s reports. From empirical study on the practical data, we have confirmed the effectiveness of using keyword information and numerical information together: (1) the effectiveness of keyword information is different by the direction of change of earning estimate; (2) the keyword of “Upward (or Downward) surprise in forecast” has strong effect to stock price return.