Viewing Market Price Discovery as an Algorithmic Process
Courant Institute,New York University
February 24, 2011
JEC 3117 - 4:00 p.m. to 5:00 p.m.
Self-organizing behavior can often be viewed as arising from a distributed process. It is natural to ask when and why it occurs. Our thesis is that an algorithmic perspective may be helpful.
One instance of such a distributed process is pricing in markets. A basic tenet of well-functioning markets is that they discover (converge toward) prices that simultaneously balance supplies and demands of all goods; these are called equilibrium prices. Further, the markets are self-stabilizing, meaning that they converge toward new equilibria as conditions change.
This talk will seek to explain why this could happen. More specifically, we describe the setting of Ongoing Markets (by contrast with the classic Fisher and Exchange markets). An Ongoing Market allows trade at non-equilibrium prices, and, as its name suggests, continues over time. The main task remaining is to specify and analyze a suitable price update rule. We consider a (tatonnement-style) rule with the following characteristics:
1. There is a separate instance of the price update procedure for each good.
2. The procedure is distributed:
(i) the instances are independent, and
ii) each instance uses limited 'local' information.
3. It is simple.
4. It is asynchronous: price updates do not have to be simultaneous.
And for appropriate markets the rule enables:
5. Fast convergence.
6. Robustness in the face of (somewhat) inaccurate data.
This talk is based on papers with Lisa Fleischer and Ashish Rastogi.
Hosted by: Dr. Elliot Anshelevich (x6491)
Last updated: February 5, 2011