This paper explores the relationship between disclosure in securities markets and the firm's need for confidentiality. Transparency plays a crucial role for both investor protection and the proper functioning of financial markets. Confidentiality protects the value of information which has been costly produced by the company and preserves private incentives for business and technological innovation. The requirement of too detailed or early disclosure in securities markets, even when aimed at greater investor protection and enhanced market efficiency, would be ultimately detrimental since it would hinder the firm's competitive capacity and weaken the system of private incentives for innovation. EU mandatory disclosure rules protect the firm's interest in confidentiality and allow public companies to refrain from – or delay – the release of the most sensitive data. The scope of these safe harbours, however, is narrow and always at risk of excessive restriction by the powers of regulatory agencies. Furthermore, when information with competitive value is concurrently significant for investors, refraining from disclosure – no matter if allowed or not by the law – hampers the firm's capacity to raise finance and makes the process of resource allocation less efficient. Selective disclosure reconciles investors' demand for information and the firm's need for confidentiality since it allows market prices to react to the information whilst also bypassing the need for public release of the relevant contents. Reconciling the tension, in turn, constitutes a desirable outcome: the securities market will be more efficient and raising finance will become less costly, especially for the most ‘secrecy sensitive’ projects. At the same time, the system of private incentives for innovation will be fully preserved.

In this paper we describe a conceptual framework and implementation of a tool that supports task-directed, distributed routine design (RD) augmented with simulation-based design testing. In our research, we leverage the modular distributed modeling (MDM) methodology to simulate the interaction of design components in an assembly. The major improvement we have made in the RD methodology is to extend it with the capabilities of incorporating remotely represented off-the-shelf components in design and simulation-based testing of a distributed assembly. The deliverable of our research is the RD-MDM platform, which is capable of automatically selecting intellectually protected off the shelf design components over the Internet, integrating these components in an assembly, running simulations for design testing, and publishing the approved design without disclosing the proprietary information.