Mining Associations on the Warsaw Stock Exchange

Identi cation of patterns in stock markets has been an important subject for many years. In the past, numerous techniques, both technical and econometric, were used to predict changes in stock markets, but dependences among all the companies listed on a stock market were considered in a limited extent. Numerous studies con rm that larger stocks items appear to in uence smaller ones and that, on a global level, most of the world's stock markets are integrated. Therefore, this study implements the association rules using a data mining approach to explore the co-movement between stock items listed on the Warsaw Stock Exchange. We believe that in order to describe and to understand market's behavior, data mining techniques are more exible in use than for instance pricing models based on a nance theory. The former seems to be more e ective for explaining market behavior without making particular assumptions.