| In Chapter 1, we consider a market signaling game in which receivers observe both the sender's costly signal as well as a stochastic grade that is correlated with the sender's type. We characterize equilibria satisfying the D1 refinement using an algorithmic approach and provide conditions under which the equilibrium is unique. When grades are sufficiently informative, the Least Cost Separating Equilibrium fails D1. Unlike gradeless models, the equilibrium depends on the prior it involves full pooling when the prior puts sufficient weight on the high type and partial pooling otherwise. We derive conditions under which the equilibrium converges to the fully efficient outcome as the proportion of high types goes to one---resolving a long-standing paradox within the signaling literature.;In Chapter 2, we study a dynamic setting in which stochastic information about a privately-informed seller's type is gradually revealed to a market of buyers. We characterize the unique equilibrium in a continuous-time framework. The equilibrium involves periods of no trade or market failure. The no-trade period ends in one of two ways: either enough good news arrives restoring confidence and markets re-open or bad news arrives making buyers more pessimistic forcing market capitulation i.e., a sell-off of low value assets. Reservation values arise endogenously from the option to sell in the future. Our model also encompasses both lemons and signaling environments---in a dynamic setting with sufficiently informative news, the two environments have the same equilibrium.;Chapter 3 explores the role of news in financial markets with asymmetrically informed traders. A single indivisible asset can be exchanged between asymmetrically informed traders whose time preference for money changes over time due to the arrival of random liquidity shocks. Meanwhile, information about the asset type is revealed gradually to uninformed traders. In equilibrium, the price is determined not only by uninformed traders' beliefs about the fundamental value of the asset, but also by expectations of future liquidity in the market. Assets are traded when market beliefs are sufficiently positive or sufficiently negative with periods of no-trade in between. The model helps to explain a number of frequently observed trading patterns. Evidence from the mortgage-backed securities market is discussed. |
