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Information Cascades: Evidence from a Field Experiment with Financial Market Professionals

Authors

  • JONATHAN E. ALEVY,

  • MICHAEL S. HAIGH,

  • JOHN A. LIST

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    • Alevy is from the Department of Resource Economics at the University of Nevada–Reno, Haigh is from the U.S. Commodity Futures Trading Commission, and List is from the Department of Economics at the University of Chicago and NBER. Thanks to the Editor (Robert Stambaugh), an associate editor, and an anonymous reviewer for sharp comments that improved the study considerably. John Di Clemente, former managing director of research at the Chicago Board of Trade, authorized this study. Also special thanks to CBOT staff Dorothy Ackerman Anderson, Frederick Sturm, and Keith Schap for their incredible support on site. Valuable comments and suggestions were provided by seminar participants at Harvard University, University of Chicago, University of Maryland, George Mason University, American University, University of Nevada at Reno, University of Texas at Dallas, the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting and Market Risk Management (St. Louis, Missouri, April 2003), the Economic Science Association International Conference, (Pittsburgh, Pennsylvania, July 2003), the Financial Management Association Annual Meeting (New Orleans, October, 2004), and the University of Copenhagen Workshop on Herding (Copenhagen, September, 2005). Nathan Berg, Liesl Koch, Michael Price, Vernon Smith, Georg Weizsacker, and Anthony Ziegelmeyer provided useful comments on the manuscript. The views expressed in this paper are those of the authors and do not in any way reflect the views or opinions of the U.S. CFTC.


ABSTRACT

Previous empirical studies of information cascades use either naturally occurring data or laboratory experiments. We combine attractive elements from each of these lines of research by observing market professionals from the Chicago Board of Trade (CBOT) in a controlled environment. Analysis of over 1,500 individual decisions suggests that CBOT professionals behave differently from our student control group. For instance, professionals are better able to discern the quality of public signals and their decisions are not affected by the domain of earnings. These results have implications for market efficiency and are important in both a positive and normative sense.

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