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Abstracts
In this paper we present a novel similarity measure method for financial data. In our approach, we propose the assessment of the similarity in a coherent hierarchical and multi-faceted way, following the general scheme where various detailed basic measures may be used like the Fermi-Dirac divergence, Bose-Einstein divergence, or our new smoothness measure. The presented method is tested on benchmark and real stock markets data.
Discipline
Journal
Year
Volume
Issue
Pages
927-931
Physical description
Dates
published
2016-05
Contributors
author
- Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland
author
- Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland
References
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- [6] S. Amari, Diferential-Geometrical Methods in Statistics, Springer Verlag, New York 1985, doi: 10.1007/978-1-4612-5056-2
- [7] A. Cichocki, R. Zdunek, A.-H. Phan, S. Amari, Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis, Wiley, Tokyo 2009, doi: 10.1002/9780470747278
- [8] I. Csiszar, in: Prague Conf. on Information Theory, Vol. A, Academia, Prague 1974, p. 73
- [9] L. Knockaert, IEEE Trans. Sign. Process. 41, 3171 (1993), doi: 10.1109/78.257248
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv129n506kz