Clustering Financial Time Series via Information-Theory Analysis and Rank Statistics
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Clustering Financial Time Series via Information-Theory Analysis and Rank Statistics
David Blokh
JPRR Vol 7, No 1 (2012); doi:10.13176/11.396 
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David Blokh
Abstract
A method of clustering of a time series set is described. Each cluster includes time series containing the same amounts of information about other time series. The method is based on information-theory analysis and rank statistics. A measure of correlation between two time series is the uncertainty coefficient (normalized mutual information). The Newman-Keuls test is used for multiple comparisons. Clustering of Tel-Aviv 25 stock exchange companies is carried out using the described method.
JPRR Vol 7, No 1 (2012); doi:10.13176/11.396 | Full Text  | Share this paper: