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HOW TO GROUP FINANCIAL DATA WITH MAXIMUM HOMOGENEITY?
2013
Emerging Markets Journal
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 points
doi:10.5195/emaj.2013.36
fatcat:6rhqlnz52bh7zmai65ftdw52rq