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Grouping may be an obstacle itself or it may have to be improved to extract better information out of a data stream. Finding trends and dividing a population into parts may be crucial for analyses. This paper offers a modified version of Fisher method that may smoothen the cut point transitions and give out better results. Proven methodology is given with a comparison with the original method. The method may be helpful in forming subgroups in financial data, possibly in technical analyses.Keywords: Grouping, Fisher Method, Trends, Cut point

HOW TO GROUP FINANCIAL DATA WITH MAXIMUM HOMOGENEITY?