Tuesday, February 01, 2005

Predicting Behavior of Stock Traders

I thought this was a fascinating little article:

Random Trading Good Predictor of Market Behavior, Study Shows
Fortunes can be made or lost on the stock exchange, a fact well illustrated recently by the dot-com bubble burst. Even in less volatile times, traders spend their days making careful decisions about what to sell and when. But new research indicates that the behavior of the stock market can be forecasted remarkably well by taking rational thought out of the equation.

J. Doyne Farmer of the Sante Fe Institute and his colleagues designed a computer model in which traders placed orders to buy and sell at random. In the simulation, the so-called "minimally intelligent agents" were subject only to the rules of the market. When the researchers tested their approach using 21 months of data from the London Stock Exchange, they found that it successfully predicted two basic market properties with surprising acuity. The model accounted for 96 percent of the variance in the spread, which is the difference between the best buying and selling prices and is the main determinant of transaction costs. It also explained three quarters of the fluctuations in the diffusion rate, which is a standard measure of financial risk.

The authors note that their results do not imply that stock traders are unintelligent. Instead they say that the report, published online this week by the Proceedings of the National Academy of Sciences, "suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations." The new model could be employed to help regulators lower transaction costs and detect irregular market behavior. --Sarah Graham


Anonymous said...

Side angle, same subject:


Theo said...

It's interesting that an article about using chaos was posted on a "phase portrait" blog by someone other than the author of the blog. :)

I'm going to argue that these two articles are not that related, but I do think that those interested in the original Scientific American abstract will enjoy this posted article. Thanks for the comment, anonymous poster.