| Web game reveals market senseBy 
      Kimberly Patch, 
      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," 
        he said.
 
 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 
        collective actions.
 
 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 
        Wakeling.
 
 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," 
        he said.
 
 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," 
        said Wakeling.
 
 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
 Funding:   Government
 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  
        arxiv.org/abs/nlin.AO/0309033
 
 
 
 
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 | November 5/12, 2003
 
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