Direct Estimation of Lead–Lag Relationships Using Multinomial Dynamic Time Warping

Katsuya Ito, Ryuta Sakemoto

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)325-342
Number of pages18
JournalAsia-Pacific Financial Markets
Issue number3
Publication statusPublished - Sep 1 2020
Externally publishedYes


  • Dynamic time warping
  • High frequency trading
  • Lead–lag relationships

ASJC Scopus subject areas

  • Finance


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