Aggregation of Diverse Information with Double Auction Trading among Minimally-Intelligent Algorithmic Agents

43 Pages Posted: 13 Jun 2019

See all articles by Karim Jamal

Karim Jamal

University of Alberta - Department of Accounting, Operations & Information Systems

Michael S. Maier

University of Alberta - Alberta School of Business

Shyam Sunder

Yale University - School of Management; Yale University - Cowles Foundation

Date Written: June 1, 2019

Abstract

Information dissemination and aggregation are key economic functions of financial markets. How intelligent do traders have to be for the complex task of aggregating diverse information (i.e., approximate the predictions of the rational expectations equilibrium) in a competitive double auction market? An apparent ex-ante answer is: intelligent enough to perform the bootstrap operation necessary for the task—to somehow arrive at prices that are needed to generate those very prices. Constructing a path to such equilibrium through rational behavior has remained beyond what we know of human cognitive abilities. Yet, laboratory experiments report that profit motivated human traders are able to aggregate information in some, but not all, market environments (Plott and Sunder 1988, Forsythe and Lundholm 1990). Algorithmic agents have the potential to yield insights into how simple individual behavior may perform this complex market function as an emergent phenomenon. We report on a computational experiment with markets populated by algorithmic traders who follow cognitively simple heuristics humans are known to use. These markets, too, converge to rational expectations equilibria in environments in which human markets converge, albeit slowly and noisily. The results suggest that high level of individual intelligence or rationality is not necessary for efficient outcomes to emerge at the market level; the structure of the market itself is a source of rationality observed in the outcomes.

Keywords: Algorithmic traders, Rational expectations, Structural rationality, Means-end heuristic, Information aggregation, Zero-intelligence agents

JEL Classification: C92, D44, D50, D70, D82, G14

Suggested Citation

Jamal, Karim and Maier, Michael and Sunder, Shyam, Aggregation of Diverse Information with Double Auction Trading among Minimally-Intelligent Algorithmic Agents (June 1, 2019). Cowles Foundation Discussion Paper No. 2182 (2019). Available at SSRN: https://ssrn.com/abstract=3403017 or http://dx.doi.org/10.2139/ssrn.3403017

Karim Jamal

University of Alberta - Department of Accounting, Operations & Information Systems ( email )

Edmonton, Alberta T6G 2R6
Canada
780-492-5829 (Phone)
780-492-3325 (Fax)

Michael Maier

University of Alberta - Alberta School of Business ( email )

2-30C Business Building
Edmonton, Alberta T6G 2R6
Canada
7802481275 (Phone)

HOME PAGE: http://https://business.ualberta.ca/about/contact-us/school-directory/michael-maier

Shyam Sunder (Contact Author)

Yale University - School of Management ( email )

165 Whitney Avenue
P.O. Box 208200
New Haven, CT 06520-8200
United States
203-432-6160 (Phone)

HOME PAGE: http://www.som.yale.edu/faculty/sunder/

Yale University - Cowles Foundation

Box 208281
New Haven, CT 06520-8281
United States

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