Web game reveals market sense
Technology Research News
The exact workings of the financial markets
are a mystery. It is clear that the collective decisions of many traders
affect financial markets, but it is less clear how traders make decisions,
and how these decisions affect each other.
Researchers from the University of Fribourg in Switzerland have
tapped the Internet to investigate speculative trading behavior and found
that people tend to employ one of two distinct strategies depending on
the complexity of a financial market. The results also show that humans
are good at filtering information.
In addition to ferreting out information about markets and human
behavior, the method could eventually be used to train financial traders,
said Joseph Wakeling, a researcher at the University of Fribourg.
The researchers used a Web-based financial game to gain results
from several hundred people playing several tens of thousands of game
turns against computer-controlled agents.
Playing the game is very simple, said Wakeling. It provides a
market price history and asks players to predict if the next price movement
will be a rise or fall.
The underlying mechanism that determines what happens is less
simple, Wakeling said. For each person there are 94 computer-controlled
players. Each player independently chooses to be a member of one of two
groups -- those predicting a rise, or those predicting a fall. Whoever
is in the smaller of the groups -- the minority group -- wins that round
and gains points. Those in the majority group lose points.
The price movement in the game is the difference in size between
the two groups, said Wakeling. "If one group -- we can call them buyers
-- is bigger, then the price rises by the size difference. If the other
[group] -- sellers -- is bigger, the market falls by the difference,"
The only information the human and computer-controlled agents
have about the market is the correct choices from the past few rounds.
Predicting the market actually means predicting which of the two groups
will be larger, said Wakeling. "We then assume that [players] will want
to join the other group, which they think will be smaller, and so by doing
this they affect the actual outcome of the market," he said.
The computer-controlled agents act as controls and make decisions
using simple, well-defined strategies. The approach allows researchers
to investigate the behavior of a single human in an environment that involves
The results showed that human players are "quite good at spotting
and exploiting market inefficiencies; they're also good at spotting what
information is superfluous and not using more than is necessary," said
When the market complexity is below a certain level most players
are able to use a logical, deductive approach to get the better of the
market, said Wakeling. As market complexity increases, however, there
is an observable limit to humans' ability to cope logically, he said.
Beyond this threshold, people have to find other methods of decision-making.
That players' logical capacity should break down like this is
not surprising, said Wakeling. What happens next is, however. "People
are quite literally repeating the same prediction many times in succession,"
More surprising, the strategy performs better than random decision-making,
said Wakeling. The open questions are what triggers the behavior change
and why the repetitive strategy works.
The researchers have two ideas that may explain the behavior.
It may be that as market complexity increases, the number of patterns
the player must bear in mind to make a logical decision simply becomes
too large to remember, said Wakeling.
Another possibility is that because fluctuations in complex markets
are generally very small, it's difficult to try out ideas without actually
changing the market situation, Wakeling said. In this case, "an attempt
to exploit a pattern can actually destroy it," he said.
Repetitive behavior may outperform random behavior for a similar
reason. "Because the market fluctuations are so small, if you change your
position, this means that your action decides what the market outcome
is," said Wakeling. "So by changing often you can put yourself at a disadvantage."
It could also be that players are picking up a different pattern
than the one they use in simple markets. Over any given time period in
a market, "there will be a slight bias in one direction -- the market
is rising overall, or falling overall," said Wakeling. "If you can work
out what the long-term trend of the market is, by repeating the same action
throughout that period you can exploit that slight imbalance," he said.
The process is probably not conscious, but instinctive, he added.
The results also suggest that there is a real limit on the human
ability to spot useful information in the markets, said Wakeling. If this
is true, "contrary to the propositions of neo-classical economics, there
will always be some inefficiencies left behind in the market," he said.
Today's relatively fast Internet connections made the experiment
possible, said Wakeling. "Our experiment was able to take place because
we now have fast Web browsers which can transmit dynamically-changing
graphics at high-speed," he said. This allowed for a graphical interface
without users having to download a program, which meant more subjects
and thus quicker data for the researchers. "You simply log onto the Web
site and you can play -- it's all there in your Web browser," said Wakeling.
The researchers used a Web-based C program to do the number crunching
and used Flash to construct the graphical interface.
The next step is to do more testing to find out why the transition
between deductive and repetitive behavior exists, and why players choose
the repetitive strategy rather than something else, said Wakeling.
The researchers' long-term goal "is to have a proper theoretical
understanding of how humans make economic decisions, and how those individual
decisions add up to the macroscopic behavior we see around us every day,"
A system to train financial traders that is based on the interactive
minority game could be developed within three or four years, said Wakeling.
Wakeling's research colleagues were Paolo Laureti, Peter Ruch
and Yi-Cheng Zhang. The work is slated for publication in Physica A.
The research was funded by the Swiss National Science Foundation.
Timeline: 3-4 years
TRN Categories: Applied Technology
Story Type: News
Related Elements: Technical paper, "The Interactive Minority
Game: a Web-Based Investigation of Human Market Interactions," slated
for publication in Physica A and posted at
November 5/12, 2003
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