By Paul Lewis Siddoway
Ben Blau and Tyler Brough do not care whether financial markets are efficient. They just care how they become efficient.
Those who buy and sell stocks know the price of a quoted share; however, the price they end up paying for it can be different. For example, a share of stock may be selling for $3 but the true value of that stock might actually be $3.10. That difference is called a pricing error. Dr. Blau and Dr. Brough want to know more about what drives such discrepancies.
The two assistant finance professors in the Jon M. Huntsman School of Business have offices next door to each other. They said they found themselves discussing such issues over lunch, in the hallway and in their offices until they eventually decided to make it a matter of study.
“In almost every conversation we had, we would gain more insight or raise new questions about the matter,” Dr. Brough said. “It seemed to be a topic worthy of a systematic investigation.”
To figure out what causes the discrepancies, they are working with the Center for High Performance Computing at Utah State University to study 50 terabytes of quoted prices and individual trades from every market in the United States, such as the New York Stock Exchange and NASDAQ.
Dr. Blau and Dr. Brough said they encourage their students to seek out “rigorous, relevant research.” The research the professors have tackled gives them the opportunity to practice what they profess and share their research with their classes.
“Our research makes our teaching more relevant,” Dr. Blau said, “and we learn things as we teach that help us be more focused in our research.”
Because they will be analyzing so much data, they expect much of their research could take them through 2013. When their conclusions are published, they hope to be able to empirically back up theories about the impact on the market caused by insider trading, derivatives trading, analyst recommendations, fragmentation, the introduction of new electronics exchanges, circuit breakers and other such factors.
Dr. Brough said their research findings could start policy debates on topics such as the actual impact of insider trading. If, after insider trading is reported, for example, they find that pricing errors are lower than before, they might suggest that Securities and Exchange Commission regulations be eased.
Traditional economic models assume that humans are rational in their decisions. For example, models assume that individuals possess the capabilities of calculating how much of their incomes to spend and save to make themselves as happy as possible. The models further assume that people also exercise the self-control to follow through with such decisions.
Several macroeconomics professors at the Jon M. Huntsman School of Business are modeling real-world spending and saving behavior that is inconsistent with traditional models. This group currently includes James Feigenbaum, Frank Caliendo, Scott Findley and Nick Guo. One interesting finding of the macroeconomics group is that of “optimal irrational behavior,” meaning optimal departures from fully rational models of saving and spending.
They have learned that some types of so-called “irrational” behavior can generate higher lifetime well-being if the behavior comes in the form of over-saving, compared to what is generally predicted in models of full rationality.
The higher lifetime well-being results from such over-saving behavior because the long-term health of an economy improves with increased saving.