mar
21
2011

CRCS Seminar: An Optimization-Based Framework for Automated Market-Making

Yiling Chen, SEAS, Harvard

CRCS Lunch Seminar
Date: Monday, March 21, 2011
Time: 11:30am – 1:-00pm
Place: Maxwell Dworkin 119

While computers have automated the operation of most financial markets, the underlying mechanism was designed for people to operate it. It is simple, not necessarily efficient, and has room for improvement. This work is an endeavor to design efficient automated market-making mechanisms that take into consideration of the logical relationships of securities.

We propose a general framework for the design of securities markets over combinatorial or infinite state spaces. The framework enables the design of computationally efficient markets tailored to an arbitrary, yet relatively small, space of securities with bounded payoff. We prove that any market satisfying a set of intuitive conditions must price securities via a convex cost function, which is constructed via conjugate duality. Rather than dealing with an exponentially large or infinite outcome space directly, our framework only requires optimization over a convex hull. By reducing the problem of automated market-making to convex optimization, where many efficient algorithms exist, we arrive at a range of new polynomial-time pricing mechanisms for various problems. We demonstrate the advantages of this framework with the design of some particular markets. We also show that by relaxing the convex hull we can gain computational tractability without compromising the market institution’s bounded budget.

This talk is based on joint work with Jacob Abernethy and Jennifer Wortman Vaughan.

Bio: Yiling Chen is an Assistant Professor of Computer Science at Harvard University. She received her Ph.D. in Information Sciences and Technology from the Pennsylvania State University. Prior to working at Harvard, she spent two years at the Microeconomic and Social Systems group of Yahoo! Research in New York City. Her current research focuses on topics in the intersection of computer science and economics. She is interested in designing and analyzing social computing systems according to both computational and economic objectives. Chen received an ACM EC outstanding paper award and an NSF Career award, and was selected by IEEE Intelligent Systems as one of “AI’s 10 to Watch” in 2011.