The project aims to understand the process of endogenous information acquisition in financial markets. Information choices are at the front of any decision making so understanding this process is of great importance to society overall. The project explores various settings of the problem from both theory and empirical perspectives. In a standard decision framework, economic agents update their beliefs based on information (signals) they acquire. While this framework is elegant and provides a solid foundation for our economic thinking, testing it directly poses a formidable task. A major problem is that information choices are not observable and, therefore, most information-based models in finance take information as an exogenous “black box”. Another problem is that information choice models with many assets and heterogeneously informed agents are generally difficult to solve and test. A few sparse contributions in financial economics either assume a simple information structure with two types of agents, informed and uninformed, (Van Nieuwerburgh and Veldkamp, 2009, 2010; Kacperczyk, van Nieuwerburgh, and Veldkamp, 2015) or they solve problems with one risky and riskless asset (Peress, 2004).
My ERC CoG project aims to endogenize information choices in rich economic structures. The individual components identify new ways to model information choices with heterogeneously informed agents and heterogeneous assets in a general equilibrium framework. They show how to match predictions of such models with the data not only qualitatively but also quantitatively. Further, they illustrate ways in which the market structure affects information choices. Finally, they provide empirical micro-foundations for information acquisition and processing in financial markets.
Providing micro-foundations for information and its endogenous acquisition is of first-order importance. From the perspective of academic research, the goal is to understand causal mechanisms that drive economic decisions. The framework in which information is not micro-founded makes it difficult to distill such causality. Establishing causal links in economic data is further important for policy design and its effectiveness. It makes it also possible to take existing modeling paradigms to address questions beyond the narrow modeling framework. The projects in the proposal are among the first to take the literature in this direction both theoretically and empirically. They also study more realistic contexts in which we observe rich heterogeneity both in terms of agents’ information and assets in which they can invest.
Upon the conclusion of the grant period, the project has managed to deliver a number of significant results. The starting part is new theory of information anchored in the heterogeneous world with multiple assets. The follow-up new theory is the information problem with market impact induced by large investors. Subsequently, the project achieved to show how the information environment drives economically important outcomes such as income inequality or the impact of foreign investors on market efficiency. From a micro-level perspective the project achieved to show how to identify private information in the market context and how to link this element to ex-ante trading decisions.
