Information Technology Reference
In-Depth Information
Who to Listen to: Exploiting Information Quality in a
ZIP-Agent Market
Dan Ladley
1
and Seth Bullock
2
1
Leeds University Business School,
University of Leeds, UK
danl@comp.leeds.ac.uk
2
School of Computing,
University of Leeds, UK
seth@comp.leeds.ac.uk
Abstract.
Market theory is often concerned only with centralised markets. In
this paper, we consider a market that is distributed over a network, allowing us to
characterise spatially (or temporally) segregated markets. The effect of this mod-
ification on the behaviour of a market populated by simple trading agents was
examined. It was demonstrated that an agent's ability to identify the optimum
market price is positively correlated with its network connectivity. A better con-
nected agent receives more information and, as a result, is better able to judge the
market state. The ZIP trading agent algorithm is modified in light of this result.
Simulations reveal that trading agents which take account of the quality of the
information that they receive are better able to identify the optimum price within
amarket.
1
Introduction
The study of the centralised market has been one of the key areas of economic research
for many years. There have been many attempts to understand the behaviour of markets
and that of the traders within them. These attempts range from analytical studies (e.g.,
[1]), to experiments on real subjects (e.g., the studies of Smith [2]).
In addition to analytical and experimental results, the use of simulation has become
increasingly important [3,4,5,6,7]. In particular simulation has allowed the modelling
of trader micro-behaviour, which would be analytically intractable and experimentally
time consuming. In virtually all of these micro studies, the market is assumed to occupy
a single location. All bids and offers are submitted in the same place, where all others
may see and respond to them. Not all markets, however, are like this. Retail markets, for
instance, are spatially embedded and consequently impose costs in terms of the time and
effort that it takes to visit other traders and acquire information. As a consequence of
this, it is usually impossible for a trader to visit
all
possible partners. Instead, the trader
will probably restrict information gathering to nearest neighbours, or key operators in
the market. In this case the market no longer has a central location to which information
is submitted and, as a result, different traders within the market may have access to
different histories of bids and offers.
