How can we effectively aggregate disparate pieces of information that are spread among many different individuals? Prediction markets, which are essentially speculative markets created or employed for the purpose of aggregating information and making predictions, are a means of addressing this issue. Their theoretical underpinning derives from the efficient market hypothesis and stems from the idea that relevant information concerning the likelihood of future events is dispersed among the opinions and intuitions of many people. While the mechanisms underlying prediction markets vary, they all offer a means of aggregating this information, whether alone or as a supplement to other mechanisms like surveys, group deliberations and expert opinion. Many of these markets are open to the public, while others are open to particular groups.

The effective use of these markets has the potential not only to help forecast events at a local, national or international level, but also to assist companies in providing, for example, improved estimates of the potential market size for a new product idea or the launch date of new products and services. They also have many potentially valuable applications for public policy. Moreover, they can be applied at a macroeconomic and microeconomic level to yield information that is valuable for government and commercial policy-makers and which can be used for a number of social purposes.

The markets have been used to forecast uncertain outcomes ranging from influenza to the spread of infectious diseases, to the demand for hospital services, to the box office success of movies, climate change, vote shares and election outcomes, to the probability of meeting project deadlines. Prediction markets can also be used as a mechanism to help market participants hedge their exposure to risk.

The success and potential of these markets in forecasting public events and corporate outcomes has generated substantial interest among social scientists, policymakers and the business community. Insights gained may in particular have many potentially valuable applications for policy when accurate forecasts are required in relation to quantifiable targets. The information provided by prediction markets may also have value in warning managers of the likelihood of weak performance in identifiable areas, and can help improve resource allocation.

Important research questions include ‘What is the impact of different types of prediction market design on their performance?’ and ‘What are the impacts of different types of reward on the level of accuracy of prediction markets?’

The editors of the Special Issue invite papers on every aspect of the study of prediction markets, but particularly encourage papers which focus on when prediction markets do well and when they do not, and why. The editors also encourage the submission of papers which offer empirical comparisons between prediction markets and other methods of forecasting in different applications, as well as the value of combining prediction markets with other forecasting methods.

Submission deadline

To submit a paper for consideration for the Special Issue, please upload your paper online and include a cover letter clearly indicating that the paper is for the Special issue on ‘Prediction markets’. The webpage for online submissions is The deadline for receipt of papers is 31 October 2017. All papers will follow the IJF’s refereeing process. Instructions for authors are provided at

Guest editors

If you require further information about the Special Issue, please contact one of the guest editors.

Leighton Vaughan Williams ([email protected])
Professor of Economics and Finance
Nottingham Business School, Nottingham Trent University

Johnnie E.V. Johnson ([email protected])
Professor of Decision and Risk Analysis
Centre for Risk Research, University of Southampton

Ming-Chien Sung ([email protected])
Professor of Risk and Decision Sciences
Centre for Risk Research, University of Southampton

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