2014 University of Illinois law Review 1521
From its founding, the federal government of the United States has been a potential gold mine for nonpublic market-moving information. By selectively disclosing this information to securities traders outside the government (or to persons who advise them), federal officials can substantially privilege certain wealthy or otherwise well-connected investors over ordinary investors in the securities market. The trading profits that can be derived from the use of this material nonpublic government information are often tremendous.
This disparity of access to government information may be unfair. But absent an identifiable personal benefit on the part of the government insider, neither the selective disclosure of government information nor the securities trading by persons on the outside constitutes a violation of the federal securities laws-even under the newly enacted Stop Trading on Congressional Knowledge (STOCK) Act. Moreover, this "political intelligence" problem appears to be worsening: in recent months, news reports about federal officials' selective disclosure of nonpublic government information have proliferated, and the SEC and DOJ are currently investigating how these leaks may have occurred.
To address the problem of selective disclosure, this Article proposes practical solutions that focus on the source of the political intelligence problem: the federal government itself. Solving-or at least reducing the amount of-selective disclosure is a complex endeavor. Equal treatment of investors is an admirable goal, but in many situations, the government has legitimate interests in communicating with members of the public and disclosing information only to certain parties. Thus, this Article attempts to carve out a middle ground that neither unduly inhibits governmental functions nor allows for patently unequal treatment of investors.
Nagy, Donna M. and Painter, Richard, "Plugging Leaks and Lowering Levees in the Federal Government: Practical Solutions for Securities Trading Based on Political Intelligence" (2014). Articles by Maurer Faculty. 2163.