Using Multi-Dimensional Dynamic Time Warping to Identify Time-Varying Lead-Lag Relationships

Autor:	Johannes Stübinger, Dominik Walter
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	time-varying lead–lag effect dynamic time warping data science big data processing multi-dimensional thermal optimal path Chemical technology TP1-1185
Zdroj:	Sensors, Vol 22, Iss 18, p 6884 (2022)
Druh dokumentu:	article
ISSN:	1424-8220
DOI:	10.3390/s22186884
Popis:	This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series. Specifically, this manuscript contributes to the literature by improving upon the use towards lead-lag estimation. Our two-step procedure computes the multi-dimensional DTW alignment with the aid of shapeDTW and then utilises the output to extract the estimated time-varying lead-lag relationship between the original time series. Next, our extensive simulation study analyses the performance of the algorithm compared to the state-of-the-art methods Thermal Optimal Path (TOP), Symmetric Thermal Optimal Path (TOPS), Rolling Cross-Correlation (RCC), Dynamic Time Warping (DTW), and Derivative Dynamic Time Warping (DDTW). We observe a strong outperformance of the algorithm regarding efficiency, robustness, and feasibility.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/bcbd2460952449449786d618642666c3 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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