University Times

When prices of stock in Internet-based companies and other speculative ventures soar, it deprives so-called “value stocks” (in blue-chip corporations, for example) of the capital needed to push their prices higher.

Result: value stock prices suffer.

When speculative stock prices tumble, the ugly image of collapsing prices discourages investors from putting their money into any kind of stocks.

Again, value stock prices suffer.

This insight — that value stocks suffer in both phases of a speculative boom/bust cycle — resulted from an exercise in the surging field of experimental economics.

The pricking of America’s late-1990s tech stocks bubble, followed by a steep decline in the Dow, provides a real-world example of the phenomenon.

Among those who conducted the research were Gunduz Caginalp, a Pitt mathematics professor, and Vernon L. Smith, an economics and law professor at George Mason University in Virginia. On Oct. 10 Smith was named a co-winner of the 2002 Nobel prize in economics.

“The award honors Vernon for a lifetime of work in developing experimental markets and understanding the forces involved in trading and investing,” said Caginalp, who has collaborated on nine papers with Smith.

Another paper on which they collaborated, detailing the value-stocks-can’t-win model summarized at the beginning of this story, will be published soon in the Journal of Psychology and Financial Markets, which Caginalp has edited for the last two years.

“I’m very happy for Vernon, who is very deserving of this great honor,” Caginalp said. “As far as my benefiting from my association with a Nobel prize-winner, it should reflect well on the journal I edit, which is still pretty young. It’s nice to be able to say that you have published the work of a Nobel prize-winner.”

Caginalp’s work with Smith has involved the design of economics experiments and analyzing the resulting data using mathematical methods.

Among the subjects they and other collaborators have tackled are the relationship between cash supply and stock trading prices, momentum as a force in investing, and financial bubbles. They have tested some of their predictions against both statistical models and professional stock traders.

“Any time that you extrapolate from experimental work to the real world, there’s a lot in the world that isn’t in the experimental setting,” Caginalp noted — for example, the impact on U.S. stock prices of the Sept. 11, 2001, terrorist attacks.

But there can be great value in experimental models that stand up to real-world conditions, according to Caginalp. “It leads to more than just effective trading strategies. It can also help in designing and, if necessary, regulating financial markets so they are stable and efficient.”

— Bruce Steele