An Artificial Stock Market
Dr. Blake LeBaron
University of Wisconsin-Madison Department of Economics
Santa Fe Institute
blebaron@facstaff.wisc.edu
2:30 pm Fri. Dec. 9 in 2310 Computer Sciences and Statistics Bldg.
In this project an artificial stock market provides an environment in which to
study the behavior of many artificially intelligent agents trying to forecast
the future behavior of a traded asset paying a random dividend. The objective
is to understand some of the phenomena possible from the interactions of
learning algorithms brought together in a simple stock market trading
environment. Traders using Holland's classifier systems build up sets of simple
rules to forecast future stock market price behavior. Successful rules are
strengthened and used more frequently while less successful rules are replaced
with new rules created by a genetic algorithm. The relationship between this
model and traditional modeling of financial markets in economics will be
discussed.