  Statistical uncertainty of different filtration techniques for market network
analysis is studied. Two measures of statistical uncertainty are discussed. One
is based on conditional risk for multiple decision statistical procedures and
another one is based on average fraction of errors. It is shown that for some
important cases the second measure is a particular case of the first one.
Statistical uncertainty for some popular market network structures is analyzed.
Results of numerical evaluation of statistical uncertainty for minimum spanning
tree, market graph, maximum cliques and maximum independent sets are given. The
most stable structures are derived.
