We analyze maximization of revenue in the dynamic and stochastic knapsack problem where a given capacity needs to be allocated by a given deadline to sequentially arriving agents. Each agent is described by a two-dimensional type that reflects his capacity requirement and his willingness to pay...

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...