  In this paper we apply the Self-Organized Map (SOM) method for clustering the
DJIA and NASDAQ100 portfolios for determination of non-linear correlations
between stocks. We represent the application of this method as alternative to
ultrametric spaces method. We have found, that SOM method is more relevant and
perspective for clustering ill-structured large databases and, in particular,
NASDAQ100, where nonlinear processing of the large data samples is required.
