The main function of replica selection in data grids is to select replica locations that show the best QoS amongst many scattered locations across the world. Estimating the QoS properly in grid environments is a challenging task because QoS attributes are different and users' preferences are different as well. Current replica selection algorithms do not providethe best QoS because they do not consider users' preferences. As a result, optimum replica selection from the data grid sites remains a significant challenge. This challenge is met here by presenting a data grid scheme based on a stock market model in which customers typically exchange an equal value of different shares according to their priorities. The scheme analyzes user preferences to select the best replica and provide a newly defined User Preference Algorithm (UPA). UPA is designed and developed specifically to meet the user's QoS, such as response time, availability and security. The algorithmic technique is based on a sound mathematical model and a supporting metric to measure User's Preferred Quality (UPQ) parameters, which integrates user preferences with the data selection process resulting in a novel multi-criteria technique. Computer simulation performance results demonstrated that the UPA performed the best compared to the competitors (the Dsystem, LfuOptimiser and Random algorithms) in terms of QoS compliance with user preferences. UPA imitates the stock market by assigning points to the users, representing QoS parameters. These points are distributed to the users prior to the data selection process. The quantity of points is dependent upon the QoS available on the sites holding the required replica. © EuroJournals Publishing, Inc. 2012.