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  1. 117 経済学研究科・経済学部
  2. 10 経済理論専攻
  3. Working Paper Series / UTokyo Price Project
  1. 0 資料タイプ別
  2. 60 レポート類
  3. 063 ワーキングペーパー

High quality topic extraction from business news explains abnormal financial market volatility

http://hdl.handle.net/2261/53027
http://hdl.handle.net/2261/53027
295c645c-0d80-4000-892d-e9927a4a9f06
名前 / ファイル ライセンス アクション
wp002.pdf wp002.pdf (2.0 MB)
Item type テクニカルレポート / Technical Report(1)
公開日 2015-05-11
タイトル
タイトル High quality topic extraction from business news explains abnormal financial market volatility
言語
言語 eng
資源タイプ
資源 http://purl.org/coar/resource_type/c_18gh
タイプ technical report
著者 Hisano, Ryohei

× Hisano, Ryohei

WEKO 98037

Hisano, Ryohei

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Sornette, Didier

× Sornette, Didier

WEKO 98038

Sornette, Didier

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Mizuno, Takayuki

× Mizuno, Takayuki

WEKO 98039

Mizuno, Takayuki

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Ohnishi, Takaaki

× Ohnishi, Takaaki

WEKO 98040

Ohnishi, Takaaki

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Watanabe, Tsutomu

× Watanabe, Tsutomu

WEKO 98041

Watanabe, Tsutomu

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著者所属
著者所属 ETH Zurich, Department of Management, Technology and Economics
著者所属
著者所属 The Canon Institute of Global Studies
著者所属
著者所属 Swiss Finance Institute
著者所属
著者所属 Department of Computer Science, Graduate school of SIE, University of Tsukuba
著者所属
著者所属 The University of Tokyo, Graduate School of Economics
抄録
内容記述タイプ Abstract
内容記述 Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affect trading and the pricing of firms in organized stock markets. In this paper we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 205 major stocks in the S&P US stock index. We show that the whole landscape of news that affect stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their "thematic" features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized fact in financial economies, namely that at certain times trading volumes appear to be "abnormally large," can be explained by the flow of news. In this sense, our results prove that there is no "excess trading," if the news are genuinely novel and provide relevant financial information.
内容記述
内容記述タイプ Other
内容記述 2012~2016年度科学研究費補助金[基盤研究(S)]「長期デフレの解明」(研究代表者 東京大学経済学研究科・渡辺努, 課題番号:24223003)
書誌情報 JSPS Grants-in-Aid for Scientific Research (S) Understanding Persistent Deflation in Japan Working Paper Series

巻 002, 発行日 2012-10
日本十進分類法
主題Scheme NDC
主題 338
出版者
出版者 UTokyo Price Project
関係URI
識別子タイプ URI
関連識別子 http://www.price.e.u-tokyo.ac.jp/researchdata/
異版あり
関連タイプ hasVersion
識別子タイプ URI
関連識別子 http://www.carf.e.u-tokyo.ac.jp/workingpaper/detail.cgi_3fd6f555bdc10cd88a3cb8823e8d92c2e3.html
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