The generation of profitable trading rules for stock market investments is a difficult task but admired problem. First stage is classifying the prone direction of the price for India Cements Stock Price Index (ICSPI) futures with several technical indicators using artificial intelligence techniques. And second stage is mining the trading rules to determined conflict among the outputs of the first stage using the evolve learning. The authors have found trading rule which would have yield the highest return over a certain time period using historical data. These groundwork results suggest that genetic algorithms are promising model yields highest profit than other comparable models and buy-and-sell strategy. Experimental results of buying and selling of trading rules were outstanding.