Rethinking Temporal Dependencies in Multiple Time Series: A Use Case in Financial Data

These days, complex systems yield copious time series data, necessitating understanding co-generation, often assessed through pairwise comparisons. However, this method lacks scalability and temporal dynamics handling. In this paper, we advocate using a temporal graph to capture contiguous effects a...

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Bibliographic Details
Main Authors: Owusu, Patrick Asante, Tajeuna, Etienne, Patenaude, Jean-Marc, Brun, Armelle, Wang, Shengrui
Format: Conference Proceeding
Language:English
Subjects:
Complex systems
Correlation
Cross-sectional patterns
Data mining
Data models
Financial data
Multiple time series
Scalability
Series trajectory
Temporal graph
Time series analysis
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Summary:These days, complex systems yield copious time series data, necessitating understanding co-generation, often assessed through pairwise comparisons. However, this method lacks scalability and temporal dynamics handling. In this paper, we advocate using a temporal graph to capture contiguous effects among multiple time series efficiently. Our two-step approach identifies patterns and temporal influences with low execution time, showcasing its potential in financial system incident prediction.
ISSN:2374-8486
DOI:10.1109/ICDM58522.2023.00156