Dywergencje bosego-einsteina w analizie podobieństw finansowych szeregów czasowych
Bose-einstein divergences for similarity analysis in financial time series

Summary/Abstract: The similarity assessment of the financial time series is the one of problems where the proper methodological choice is very important. The typical correlation approach can lead to misleading results. Often the similarity score is contrary to the visual observations, expert’s knowledge and even a common sense. The reasons of such situations can be associated with the properties of the correlation measure and its adequateness for analyzed data, as well as in terms of methodology aspects. In this article, we point these disadvantages associated with the use of correlation to assess the similarity of financial time series as well as we propose the alternative solution based on divergence measures. In particular, we focus on the BoseEinstein divergence. The practical experiments with simulated data confirm the validity of our concept.

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