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Applications of Signature Methods to Market Anomaly Detection. (arXiv:2201.02441v1 [q-fin.CP])
Jan. 10, 2022, 2:10 a.m. | Erdinc Akyildirim, Matteo Gambara, Josef Teichmann, Syang Zhou
cs.LG updates on arXiv.org arxiv.org
Anomaly detection is the process of identifying abnormal instances or events
in data sets which deviate from the norm significantly. In this study, we
propose a signatures based machine learning algorithm to detect rare or
unexpected items in a given data set of time series type. We present
applications of signature or randomized signature as feature extractors for
anomaly detection algorithms; additionally we provide an easy, representation
theoretic justification for the construction of randomized signatures. Our
first application is based …
More from arxiv.org / cs.LG updates on arXiv.org
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