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

Author

Listed:
  • Katsuya Ito

    (The University of Tokyo)

  • Ryuta Sakemoto

    (YJFX, Inc.
    Keio University)

Abstract

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.

Suggested Citation

  • Katsuya Ito & Ryuta Sakemoto, 2020. "Direct Estimation of Lead–Lag Relationships Using Multinomial Dynamic Time Warping," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(3), pages 325-342, September.
    • Handle: RePEc:kap:apfinm:v:27:y:2020:i:3:d:10.1007_s10690-019-09295-z
    DOI: 10.1007/s10690-019-09295-z
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    References listed on IDEAS

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    More about this item

    Keywords

    Lead–lag relationships; High frequency trading; Dynamic time warping;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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