DIMACS Workshop on Markets as Predictive Devices (Information Markets)

Event Detail

General Information
Wednesday, February 2, 2005 - Friday, February 4, 2005
Days of Week:
Target Audience:
Academic and Practice
DIMACS Center, Rutgers University, Piscataway, NJ
Event Details/Other Comments:

For decades, economists have studied an astonishing "side effect''
of financial and wagering markets: their ability to serve as highly accurate forecasting devices. This workshop aims to explore the use of markets as a substitute for, or complement to, more traditional forecasting tools. We will examine how information flows from traders to the market and back again, how market mechanisms process information, how market prices communicate information and forecasts, and what mechanisms best foster accurate and statistically-testable predictions. The workshop will bring together researchers and practitioners from a variety of relevant fields, including economics, finance, computer science, and statistics, in both academia and industry, to discuss the state of the art today, and the challenges and prospects for tomorrow.
A market designed from the outset for information gathering and forecasting is called an information market. Information markets can be used to elicit a collective estimate of the expected value or probability of a random variable, reflecting information dispersed across an entire population of traders. The market prediction is not usually an average or median of individual opinions, but is a complex summarization reflecting the game-theoretic interplay of traders as they obtain and leverage information, and as they react to the actions of others obtaining and leveraging their own information, etc. In the best case scenario, the market price reflects a forecast that is a perfect Bayesian integration of all the information spread across all of the traders, properly accounting even for redundancy. This is the equilibrium scenario called rational expectations in the economics literature, and is the assumption underlying the strong form of the efficient markets hypothesis in finance.
The degree to which market forecasts approach optimality in practice, or at least surpass other known methods of forecasting, is remarkable. Supporting evidence can be found in empirical studies of options markets, commodity futures markets, political stock markets, sports betting markets, horse racing markets, market games, laboratory investigations of experimental markets, and field tests. In nearly all these cases, to the extent that the financial instruments or bets are tied to real-world events, market prices reveal a reliable forecast about the likely unfolding of those events, often beating expert opinions or polls.
Despite a growing experimental literature, many questions remain regarding how best to design, deploy, analyze, and understand information markets, including both technical challenges (e.g., designing combinatorial exchanges and social challenges (e.g., overcoming legal and ethical concerns). The search for answers will benefit from input from economists (including specialists in mechanism design, experimental economics, financial markets, wagering markets, and rational expectations theory), statisticians and decision theori