Abstract
Similarity assessment between financial time series is one of problems where the proper methodological choice is very important. The typical correlation approach can lead to misleading results. Often the similarity measure is opposite to the visual observations, expert’s knowledge and even a common sense. The reasons of that can be associated with the properties of the correlation measure and its adequateness for analyzed data, as well as in terms of methodological aspects. In this article, we indicate disadvantages associated with the use of correlation to assess the similarity of financial time series and propose an alternative solution based on divergence measures. In particular, we focus on the Bose-Einstein divergence. The practical experiments conducted on simulated and real data confirmed our concept.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Amari, S.: Diferential-Geometrical Methods in Statistics. Springer (1985)
Anscombe, F.J.: Graphs in statistical analysis. The American Statistician 27, 17–21 (1973)
Bashashati, A., Fatourechi, M., Ward, R., Birch, G.: A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals. Journal of Neural Engineering 4, 32–57 (2007)
Cardoso, J.-F., Comon, P.: Independent component analysis, a survey of some algebraic methods. In: Proc. ISCAS Conference Atlanta, vol. 2, pp. 93–96 (1996)
Cichocki, A., Zdunek, R., Amari, S.-i.: Csiszár’s Divergences for Non-negative Matrix Factorization: Family of New Algorithms. In: Rosca, J.P., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds.) ICA 2006. LNCS, vol. 3889, pp. 32–39. Springer, Heidelberg (2006)
Cichocki, A., Zdunek, R., Phan, A.-H., Amari, S.: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis. John Wiley (2009)
Csiszar, I.: Information measures: A critical survey. In: Prague Conference on Information Theory, vol. A, pp. 73–86. Academia Prague (1974)
Krutsinger, J.: Trading Systems: Secrets of the Masters. McGraw-Hill (1997)
Luo, Y., Davis, D., Liu, K.: A Multi-Agent Decision Support System for Stock Trading. The IEEE Network Magazine Special Issue on Enterprise Networking and Services 16(1) (2002)
Rodgers, J.L., Nicewander, W.A.: Thirteen ways to look at the correlation coefficient. The American Statistician 42(1), 59–66 (1988)
Samorodnitskij, G., Taqqu, M.: Stable non-Gaussian random processes: stochastic models with infinitive variance. Chapman and Hall, New York (1994)
Therrien, C.W.: Discrete Random Signals and Statistical Signal Processing. Prentice Hall, New Jersey (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Szupiluk, R., Ząbkowski, T. (2013). Similarity Analysis Based on Bose-Einstein Divergences for Financial Time Series. In: Tomassini, M., Antonioni, A., Daolio, F., Buesser, P. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2013. Lecture Notes in Computer Science, vol 7824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37213-1_43
Download citation
DOI: https://doi.org/10.1007/978-3-642-37213-1_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37212-4
Online ISBN: 978-3-642-37213-1
eBook Packages: Computer ScienceComputer Science (R0)