On the Gains and Losses of Speculation in Equilibrium Markets
By Tuomas Sandholm and
Fredrik Ygge. To appear in
Proceedings of the Fifteenth International Conference on Artificial Intelligence,
The paper is a rather technical paper written for people with background
in computer science and computational markets.
In computational markets utilizing algorithms that establish a market equilibrium
(general equilibrium), competitive behavior is usually assumed: each
agent makes its demand (supply) decisions so as to maximize its utility
(profit) assuming that it has no impact on market prices. However, there
is a potential gain from strategic behavior (via speculating about
others) because an agent does affect the market prices, which affect the
supply/demand decisions of others, which again affect the market prices
that the agent faces.
This paper presents a method for computing the maximal advantage of
speculative behavior in equilibrium markets. Our analysis is valid for
a wide variety of known market protocols. We also construct demand revelation
strategies that guarantee that an agent can drive the market to an equilibrium
where the agent's maximal advantage from speculation materializes.
Our study of a particular market shows that as the number of agents
increases, gains from speculation decrease - often turning negligible
already at moderate numbers of agents. The study also shows that under
uncertainty regarding others, competitive acting is often close to optimal,
while speculation can make the agent significantly worse off - even if
the agent's beliefs are just slightly biased. Finally, protocol dependent
game theoretic issues related to multiple agents counterspeculating are
Note: This paper is under copyright of IJCAI.
The entire paper in zipped PostScript format.
Last edited May 5th 1997 by email@example.com.