医療データベース研究の信頼性・透明性・再生性を高めるための研究の手続きに関する、ISPOR&ISPE合同タスクフォースのリコメンデーション「Good Practices for Real-World Data Studies of Treatment and/or Comparative Effectiveness: Recommendations from the Joint ISPOR-ISPE Special Task Force on Real-World Evidence in Health Care Decision Making 」のまとめです。REQUIRE研究会での報告内容になります。
医療データベース研究の信頼性・透明性・再生性を高めるための研究の手続きに関する、ISPOR&ISPE合同タスクフォースのリコメンデーション「Good Practices for Real-World Data Studies of Treatment and/or Comparative Effectiveness: Recommendations from the Joint ISPOR-ISPE Special Task Force on Real-World Evidence in Health Care Decision Making 」のまとめです。REQUIRE研究会での報告内容になります。
Dynamic Time Warping を用いた高頻度取引データのLead-Lag 効果の推定Katsuya Ito
This paper investigates the Lead-Lag relationships in high-frequency data.
We propose Multinomial Dynamic Time Warping (MDTW) that deals with non-synchronous observation, vast data, and time-varying Lead-Lag.
MDTW directly estimates the Lead-Lags without lag candidates. Its computational complexity is linear with respect to the number of observation and it does not depend on the number of lag candidates.
The experiments adopting artificial data and market data illustrate the effectiveness of our method compared to the existing methods.
Dynamic Time Warping を用いた高頻度取引データのLead-Lag 効果の推定Katsuya Ito
This paper investigates the Lead-Lag relationships in high-frequency data.
We propose Multinomial Dynamic Time Warping (MDTW) that deals with non-synchronous observation, vast data, and time-varying Lead-Lag.
MDTW directly estimates the Lead-Lags without lag candidates. Its computational complexity is linear with respect to the number of observation and it does not depend on the number of lag candidates.
The experiments adopting artificial data and market data illustrate the effectiveness of our method compared to the existing methods.