The provision of real-time and highly accurate information in large-scale distributed systems is technically difficult and approximations imply uncertainty. In economic science, however, reliable information about markets, its specifications, and the behavior of its participants is essential for sophisticated and efficient negotiation strategies. There is the need for a system that provides and allows consulting an overall knowledge of economic information in distributed markets, while managing the accuracy of information for the user. This paper evaluates the influences of uncertainties for information retrieval within distributed Grid markets. It proposes an uncertainty management component for a Decentralized Market Information System (DMIS), which regulates the accuracy of information and the number of messages for the retrieval of economic data from a scalable market. First, we analyze the properties and the completeness of information in Grid markets. Therefore, we simulate Grid market specific scenarios under complete and incomplete information provision by varying the information accessibility. The results confirm the influence of the accuracy on the stability of the market. Based on these results, an optimization mechanism, which uses approximations is introduced for the retrieval of information. The approximations are controlled by the uncertainty management to find a trade-off between the amount of messages and the accuracy of information.