This article models, and experimentally simulates, the free-rider problem in a takeover when the raider has the option to "resolicit," that is, to make a new offer after an offer has been rejected. In theory, the option to resolicit, by lowering offer credibility, increases the dissipative losses associated with free riding. The outcomes of our experiment support this prediction and produce losses from free riding even higher than theoretically predicted. These dissipation losses reduce raider gains to less than 3% of synergy value of the acquisition

This article models, and experimentally simulates, the free-rider problem in a takeover when the raider has the option to “resolicit,” that is, to make a new offer after an offer has been rejected. In theory, the option to resolicit, by lowering offer credibility, increases the dissipative losses associated with free riding. The outcomes of our experiment support this prediction and produce losses from free riding even higher than theoretically predicted. These dissipation losses reduce raider gains to less than 3% of synergy value of the acquisition

In this paper, we develop a dynamic model of institutional share dumping surrounding control events. Institutional investors sometimes dump shares, despite trading losses, in order to manipulate share prices and trigger activism by “relationship” investors. These institutional investors are motivated to trade not only by trading profits but also by a desire to protect the value of their inventory and to disguise the quality of their own information. Relationship investor profit from targeting firms both by improving firm performance and by generating private information.

We consider a competitive and perfect financial market in which agents have heterogeneous cash flow valuations. Instead of assuming that agents are endowed with rational expectations, we model their behavior as the product of adaptive learning. Our results demonstrate that adaptive learning affects security design profoundly, with securities mispriced even in the long run and optimal designs trading off underpricing against intrinsic value maximization. The evolutionary dominant security design calls for issuing securities that engender large losses with a small but positive probability, but that otherwise produce stable payoffs, almost the exact opposite of the pure state claims that are optimal in the rational expectations framework.