Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-22dnz Total loading time: 0 Render date: 2024-04-28T13:30:58.985Z Has data issue: false hasContentIssue false

18 - Information (in)efficiency in prediction markets

Published online by Cambridge University Press:  09 July 2009

Erik Snowberg
Affiliation:
Economist
Justin Wolfers
Affiliation:
Assistant Professor of Business and Public Policy Wharton School University of Pennsylvania
Eric Zitzewitz
Affiliation:
Assistant Professor of Economics Stanford Business School
Leighton Vaughan Williams
Affiliation:
Nottingham Trent University
Get access

Summary

Introduction

This chapter examines a new class of markets at the intersection of traditional betting and traditional financial markets. We call these ‘prediction markets’. Like both financial and betting markets, prediction markets focus on uncertain outcomes and involve trading in risks. Prices from these markets establish forecasts about the probabilities, mean and median outcomes, and correlations among future events. These prices have been used to accurately predict vote shares in elections, the box office success of Hollywood movies and the probability that Saddam Hussein would be deposed by a certain date. Other names for these markets include ‘virtual stock markets’, ‘event futures’, and ‘information markets’.

Financial economists have long known about the information-aggregating properties of markets. Indeed, the efficient markets hypothesis, a centrepiece of financial theory, can be stated simply as, ‘market prices incorporate all available information’. While financial instruments can be very complex, prediction markets tend to be analytically simple. Their current simplicity, however, belies their powerful potential future as a way to hedge against geopolitical and other forms of risk as envisioned by Athanasoulis, Shiller and van Wincoop (1999) and Shiller (2003).

Currently, most prediction markets are quite small, with turnover ranging from a few thousand dollars on the early political markets run by the University of Iowa, to several million bet in the 2004 election cycle on TradeSports, to hundreds of millions bet on the announcement of economic indicators in Goldman Sachs and Deutsche Bank's ‘Economic Derivatives’ market.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aït-Sahalia, Yacine, Wang, Yubo and Yared, Francis (2001) ‘Do Options Markets Correctly Price the Probabilities of Movement of the Underlying Asset?’, Journal of Econometrics, 102, pp. 67–110CrossRefGoogle Scholar
Athanasoulis, Stefano, Shiller, Robert and Wincoop, Eric (1999) ‘Macro Markets and Financial Security’, Economic Policy Review, 5, pp. 21–39Google Scholar
Berg, Joyce, Forsythe, Robert, Nelson, Forrest and Rietz, Thomas (2001) ‘Results from a Dozen Years of Election Futures Markets Research’, in Plott, Charles and Smith, Vernon (eds.), Handbook of Experimental Economic Results, New York: Elsevier ScienceGoogle Scholar
Berg, Joyce and Rietz, Thomas (2003) ‘Prediction Markets as Decision Support Systems’, Information Systems Frontiers, 5(1), pp. 79–93CrossRefGoogle Scholar
Camerer, Colin (1998) ‘Can Asset Markets be Manipulated? A Field Experiment with Racetrack Betting’, Journal of Political Economy, 106(3), pp. 457–82CrossRefGoogle Scholar
Chen, Kay-Yut and Plott, Charles (2002) ‘Information Aggregation Mechanisms: Concept, Design and Field Implementation for a Sales Forecasting Problem’, Social Science Working paper, 1131, Pasadena: California Institute of TechnologyGoogle Scholar
Hanson, Robin (1999) ‘Decision Markets’, IEEE Intelligent Systems, 14(3), pp. 16–19Google Scholar
Heckman, James J. (1979) ‘Sample Selection Bias as a Specification Error’, Econometrica, 47(1), pp. 153–61CrossRefGoogle Scholar
Leigh, Andrew, Wolfers, Justin and Zitzewitz, Eric (2003) ‘What do Financial Markets Think of War in Iraq?’, NBER Working Paper, 9587
Manski, Charles (2004) ‘Interpreting the Predictions of Prediction Markets’, NBER Working Paper, 10359, March
Ortner, Gerhard (1998) ‘Forecasting Markets – An Industrial Application’, Technical University of Vienna, mimeoGoogle Scholar
Pennock, David, Lawrence, Steve, Giles, C. Lee and Nielsen, Finn Arup (2001) ‘The Real Power of Artificial Markets’, Science, 291, pp. 987–8CrossRefGoogle ScholarPubMed
Rhode, Paul and Strumpf, Koleman (2004) ‘Historical Prediction Markets: Wagering on Presidential Elections’, Journal of Economic Perspectives, 18(2), pp. 127–42CrossRefGoogle Scholar
Servan-Schreiber, Emile, Wolfers, Justin, Pennock, David and Galebach, Brian (2004) ‘Prediction Markets: Does Money Matter?’, Electronic Markets, 14(3), pp. 243–51CrossRefGoogle Scholar
Shiller, Robert (2003) The New Financial Order: Risk in the Twenty-First Century, Princeton: Princeton University PressGoogle Scholar
Snowberg, Erik and Wolfers, Justin (2004) ‘Understanding the Favorite-Longshot Bias: Risk Preferences versus Misperceptions’, University of Pennsylvania, mimeoGoogle Scholar
Strumpf, Koleman (2004) ‘Manipulating the Iowa Political Stock Market’, University of North Carolina, mimeoGoogle Scholar
Tetlock, Paul (2004) ‘How Efficient are Information Markets? Evidence from an Online Exchange’, University of Texas at Austin, mimeoGoogle Scholar
Wolfers, Justin and Andrew, Leigh (2002) ‘Three Tools for Forecasting Federal Elections: Lessons from 2001’, Australian Journal of Political Science, 37(2), pp. 223–40CrossRefGoogle Scholar
Wolfers, Justin and Zitzewitz, Eric (2004) ‘Prediction Markets’, Journal of Economic Perspectives, 18(2), pp. 107–26CrossRefGoogle Scholar
Wolfers, Justin and Zitzewitz, Eric (2005) ‘Interpreting Prediction Market Prices as Probabilities’, University of Pennsylvania, mimeoGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×