Risk/return management has not only evolved as one of the key success factors for enterprises especially in the financial services industry, but is in the times of the financial crisis crucial for the survival of a company. It demands powerful and at the same time flexible computational resources making it an almost ideal application for service-oriented computing concepts. An essential characteristic of service-oriented infrastructures is that computational resources can be accessed on demand and paid per use. Taking the estimation of covariances for a portfolio of risky investment objects as an example, we propose quantification for the economic value of fast risk/return management calculations. Our model analyzes the influence factors on the optimal computing capacity dedicated to these calculations and reveals interesting insights in how far the optimal computing capacity depends on market parameters. Our main result is that more volatile markets require a lower computing capacity as the optimal computing capacity depends positively on changes of the market risk but negatively on the risk itself.