The paper deals with issues associated with identification of stocks generating abnormal returns. Following the findings of a finance theory regarding portfolio tilting, a set of price-related stocks' attributes was analyzed. The analysis was conducted with the help of rough sets methodology which allows to distinguish "important" attributes for problem description, and to generate decision rules which can be later used to predict stocks' performance. Validity of the approach was tested on the Toronto Stock Exchange data.