Evidence indicates that shares of companies belonging to the same economic sector have similar returns over time, since they would be exposed to similar economic-financial and technical-operational variables. Portfolio managers, in general, use this evidence in their daily valuations in order to find the best investment alternatives. However, in most cases, there isn`t a theoretical and mathematical background proving this relationship between stocks exists. The objective of this dissertation is to determine whether, for a group of stocks classified as among the most important of the Brazilian stock market, the daily closing prices that behave similarly correspond to companies in the same economic sector. To test this hypothesis, various clustering methods were evaluated and applied to the dissimilarity matrix calculated for the analyzed data, which is determined using different non-parametric techniques for calculating the dependency between data. The models were compared and the best selected by applying clustering validation index.