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High quality topic extraction from business news explains abnormal financial market volatility
http://hdl.handle.net/2261/53027
http://hdl.handle.net/2261/53027295c645c-0d80-4000-892d-e9927a4a9f06
名前 / ファイル | ライセンス | アクション |
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wp002.pdf (2.0 MB)
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Item type | テクニカルレポート / Technical Report(1) | |||||
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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 | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||
資源タイプ | technical report | |||||
著者 |
Hisano, Ryohei
× Hisano, Ryohei× Sornette, Didier× Mizuno, Takayuki× Ohnishi, Takaaki× Watanabe, Tsutomu |
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著者所属 | ||||||
値 | ETH Zurich, Department of Management, Technology and Economics | |||||
著者所属 | ||||||
値 | The Canon Institute of Global Studies | |||||
著者所属 | ||||||
値 | Swiss Finance Institute | |||||
著者所属 | ||||||
値 | Department of Computer Science, Graduate school of SIE, University of Tsukuba | |||||
著者所属 | ||||||
値 | 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 |
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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 |