In the present paper, a trading strategy based on pattern recognition is optimized by means of a genetic algorithm. The genetic algorithm is used to determine decisions of buy/sell based on the patterns found through time for a portfolio in the stock market. The predominant algorithms used in this work were the K-means clustering algorithm to find the patterns in different time lapses, and the genetic algorithm for optimization. The results are supported by simulations using a selected shares of the Mexican stock market.