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荻原研究室
Showing the original Japanese · View translation
ランダムに変化する現象を統計で捉え、金融データの分析に生かす研究室。
AboutAbout the lab
ランダムな動きを、統計で読み解く。
荻原研究室は、
確率過程は、
株の
ニューラル・ネットワークで
Key terms
- 確率過程
- 時間とともに
ランダムに 変化する 量を、 数学の モデルと して 表した もの。 株価の 動きなどに 使う - 高頻度
データ - 一日の
うちの 株の 全取引のように、 とても 細かい 時間の 間隔で 記録された データ - 確率微分方程式
- ランダムな
ゆらぎを 含む変化を 表す方 程式。 株価の モデルと して 使われる
ResearchResearch themes
確率過程に
*Illustrative image高頻度データの統計解析
高頻度
*Illustrative imageニューラル・ネットワークで株価をモデル化
高頻度
*Illustrative image板情報の点過程モデリング
取引が
*Illustrative image推定の理論的な最適性
推定の
MembersFaculty
- Associate Professor荻原 哲平Publications ↗
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Market centre in Tokyo stock exchange” ehnmark / CC BY 2.0 (cropped)
- 高頻度
データの 統計解析: “SamplePathsDiffusionProcess” Jbusemey / CC0 (cropped) - ニューラル・ネットワークで
株価を モデル化: “Artificial Neural Network Example” Jhedengren / CC BY-SA 4.0 (cropped) - 板情報の
点過程モデリング: “Order Book, depth of market” RuppaZakir / CC BY-SA 4.0 (cropped) - 推定の
理論的な 最適性: “Wiener process 3d” Sullivan.t.j / CC BY-SA 3.0 (cropped)
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