Identification of patterns in the stock market has been an important subject for many years. In the past, a numerous techniques, both technical and econometrics, were used to predict changes in the stock market, but dependency among alll the companies listed on a Polish Stock Exchange were considered in a limited extent.  Numerous studies confirm that that larger stock items appear to lead smaller ones and that, on global level, most of the world’s stock markets are integrated. Therefore, this study implements the association rules as a data mining approach to explore the co-movement between stock items listed on Warsaw Stock Echange.  We belive that to describe and to understand market’s behavior, data mining tools are more flexible to use than for instance the pricing models based on corporate finance theory, because the former seems to be more effective for explaining market behavior without making particuliar assumptions.

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