You are here

(PhD) Learning and Information Aggregation in Markets and Games

Spring 2011 PHD Course

B9210-012: (PhD) Learning and Information Aggregation in Markets and Games

R - Full Term, 04:15PM to 07:15PM
Location: URI 140

Instructor: Bogachan Celen

The aim of this course is to introduce students to the vast literature on learning and information aggregation in markets and games. The course starts with a brief review of the basic concepts and technical tools required to understand the papers to be covered. In the first part of the course, I intend to discuss information aggregation in pure information externality
environments and the welfare implications arising thereof. The second part focusses on learning in financial markets with an emphasis to market microstructure and rational expectations equilibrium. Finally, the last part of the course is built around information aggregation in strategic environments. In particular, information aggregation in auctions and elections, learning in games and experimentation in markets will be emphasized.
The goal of the course is to expose students to the literature and encourage future research in the area. Therefore, students will be required to actively participate in class: they are required to present a research paper and write a research proposal that reviews the related literature, motivates the question and discuss the methodology to be employed. Although the course has a theoretical content, I believe it is also useful for the students who want to
pursue empirical research in the area.
The course is most suitable to finance and economics students who successfully completed first year requirements of the Ph.D. program. Although a solid understanding of probability theory, stochastic processes and some analysis is a plus, it is not required for the course, with the understanding that the students are willing to strengthen their technical skills
throughout the course.