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.

中文翻译：

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使用多项动态时间规整直接估计超前-滞后关系

本文研究了高频数据中的超前-滞后关系。我们提出多项动态时间扭曲 (MDTW)，用于处理非同步观测、大量数据和时变超前滞后。MDTW 直接估计没有滞后候选的超前滞后。它的计算复杂度与观察次数呈线性关系，并且不依赖于滞后候选的数量。采用人工数据和市场数据的实验说明了我们的方法与现有方法相比的有效性。