Financial Time series: motif discovery and analysis using VALMOD
Cartwright, Eoin, Crane, MartinORCID: 0000-0001-7598-3126 and Ruskin, Heather J.
(2019)
Financial Time series: motif discovery and analysis using VALMOD.
In: International Conference on Computational Science, 12-14 June, 2019, Faro, Portugal.
ISBN 978-3-030-22749-4
Motif discovery and analysis in time series data-sets have a wide-range of applications from genomics to finance. In consequence, development and critical evaluation of these algorithms is required with the focus not just detection but rather evaluation and interpretation of overall significance. Our focus here is the specific algorithm, VALMOD, but algorithms in wide use for motif discovery are summarised and briefly compared, as well as typical evaluation methods with strengths. Additionally, Taxonomy diagrams for motif discovery and evaluation techniques are constructed to illustrate the relationship between different approaches as well as inter-dependencies. Finally evaluation measures based upon results obtained from VALMOD analysis of a GBP-USD foreign exchange (F/X) rate data-set are presented, in illustration.
Rodrigues, João M. F., Cardoso, Pedro J. S., Monteiro, Jânio and Lam, Roberto, (eds.)
Conference proceedings ICCS 2019. Lecture Notes in Computer Science (LNCS)
11540(5).
Springer. ISBN 978-3-030-22749-4