Risk/return management has evolved as one of the key success factors for enterprises especially in the financial services industry. It is highly demanding in terms of business requirements and technical resources, making it an almost ideal application for grid computing concepts. In this paper we analyze the value proposition of grid computing for risk/return management. We focus on a specific problem?the estimation of covariance matrices?and propose a model to quantify the benefits and cost of the corresponding calculations. Our model not only makes a contribution to understand the business value of grid computing in the domain of risk/return management, it also constitutes a building block for the development of economic resource allocation mechanisms.