  Main purpose of distance based portfolio constructions is in portfolio
imitation. Here we construct portfolio based on Hellinger distance from normal
distribution. We empirically found that minimum of this distance drastically
varies from market to market. Thus we suppose that it may be regarded as a form
of market invariant, in a sense of helpful tool for market segmentation. We
analyze its sensitivity. Though mean sensitivity was small it showed extreme
sensitivity in some cases.
