Multiway Similarity Approach Based on Divergence Functions and Smoothness Measure

• Authors: R. Szupiluk , T. Sobon
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

05.45.Tp; 05.40.Ca; 07.05.Kf; 07.05.Mh

Discipline

• 05.40.Ca: Noise
• 05.45.Tp: Time series analysis
• 07.05.Mh: Neural networks, fuzzy logic, artificial intelligence
• 07.05.Kf: Data analysis: algorithms and implementation; data management(for data analysis in nuclear physics, see 29.85.-c)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2016
• Volume: 129
• Issue: 5
• Pages: 927-931

Dates

published

2016-05

Contributors

author

R. Szupiluk

• Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland

author

T. Sobon

• Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland

References

• [1] J. Krutsinger, Trading Systems: Secrets of the Masters, McGraw-Hill, New York 1997
• [2] J.L. Rodgers, W.A. Nicewander, Am. Statistic. 42, 59 (1988)
• [3] C.W. Therrien, Discrete Random Signals and Statistical Signal Processing, Prentice Hall, New Jersey 1992
• [4] A.N. Shiryaev, Essentials of Stochastic Finance: Facts, Models, Theory, World Sci., Singapore 1999, doi: 10.1142/3907
• [5] R. Szupiluk, P. Wojewnik, T. Zabkowski, Noise Detection for Ensemble Methods, Lecture Notes in Artificial Intelligence, Vol. 6113, Springer, Heidelberg 2010, doi: 10.1007/978-3-642-13208-7_59
• [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

Identifiers

DOI

10.12693/APhysPolA.129.927