いくらかサーベイしたのでそれを報告しときます．
興味あったら読んでみてね．
・ニュースが株価に与える影響分析
http://www.spss.co.jp/ronbun/2004-pd/2004-05.pdf
大ちゃん曰く「内容薄い」らしいんだけど（笑）
少しは見るところあるかと思います．
論文じゃなくて学校のゼミ用資料みたいで
目的も「IRのために分析を利用する」だから若干違うかもなんですが，
やってることはライブドア関連のニュースに出て来るキーワードを
クラスタリングして，クラスタごとに株価に与える影響が
どんな感じかを調べています．
結果，クラスタごとにボラティリティ（株価の動きの激しさ）が
違いましたね，と言うお話．
一番問題なのはライブドアにスペシフィックなことを分析したところで
一般的な株価の影響云々，って言い方は出来ないだろってとこだと思う．
ライブドアの事件はインパクトが大き過ぎたし，
あまりに特殊性があり過ぎると思うので．
二番目に問題なのは，ニュースソースの絶対量かな．
１クラスタごとに２，３０個ってどうなんだろうか．
そもそもクラスタ分析するのに必要なデータ量が他の会社だと
集まらない気がする．
いいのかな？こういう分析をやったことないからよくわかんない．
でも中で「有意っぽい結果じゃない」的なことが書いてあるから
結局量が足りてないし，そもそもクラスタごとに
ボラティリティが違うってほんとに言えるのかどうかは怪しげ．
ただ一番面白いと思ったのは
「同じ内容の情報が流れ続けるとボラティリティが下がる」
って書いてるとこ．納得出来るし，ここは信用出来そうな．
大量のニュースを処理するとなればニュースの重複は
困った問題になりそうだけど，
その解決方法の１つとして，逆にボラティリティの低さから
ニュースの重複を予想することが出来れば，
その問題の解決の糸口になるのかなとか思いました．
もしかしたら使うことになる考え方かもしれないな．
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psWhen is your next talk scheduled?
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