We use the tools of mechanism design, combined with the theory of risk measures, to analyze how a cash constrained owner of an asset with known stochastic returns raises capital from a population of investors that differ in their risk aversion and budget constraints. The issuer partitions the...

We derive conditions on the learning environment - which encompasses both Bayesian and non-Bayesian processes - ensuring that an efficient allocation of resources is achievable in a dynamic allocation environment where impatient, privately informed agents arrive over time, and where the designer...

We derive the revenue maximizing allocation of m units among n symmetric agents who have unit demand, and who take costly actions that influence their values before participating in the mechanism. The allocation problem with costly actions can be represented by a reduced form model where agents...

We derive the revenue maximizing mechanism for a risk-neutral seller whofaces Yaari's [1987] dual risk-averse bidders. The optimal mechanism offers "full-insurance" in the sense that each agent's utility is independent of other agents'reports. The seller excludes less types than under risk...

Arne Ryde Memorial Lectures Series List -- Contents -- About the Arne Ryde Foundation -- Acknowledgments -- 1 Introduction -- 2 The Sequential Assignment of Heterogeneous Objects -- 3 Dynamic Revenue Maximization with Heterogeneous Objects -- 4 The Stochastic and Dynamic Knapsack Model -- 5...

We study a multi-dimensional collective decision under incomplete information. Agents have Euclidean preferences and vote by simple majority on each issue (dimension), yielding the coordinate-wise median. Judicious rotations of the orthogonal axes -- the issues that are voted upon -- lead to...