Experimental Political Betting Markets and the 2004 Election.

Betting on elections has been of interest to economists and political scientists for some time. We recently persuaded TradeSports to run experimental contingent betting markets, in which one bets on whether President Bush will be re-elected, conditional on other specified events occurring. Early results suggest that market participants strongly believe that Osama bin Laden's capture would have a substantial effect on President Bush's electoral fortunes, and interestingly that the chance of his capture peaks just before the election. More generally, these markets suggest that issues outside the campaign, like the state of the economy, and progress on the war on terror , are the key factors in the forthcoming election.Other Topics

Decision Markets for Policy Advice

The main cause of bad policy decisions is arguably a lack of information. Decisionmakers often do not make use of relevant information about the consequences of the policies they choose. The problem, however, is not simply that public officials do not exploit readily available information. It is also that they do not take full advantage of creative mechanisms that could expand the supply of policy-relevant information. Among the most innovative and potentially useful information-generating mechanisms are speculative markets. Speculative markets produce public information about the perceived likelihood of future events as a natural byproduct of voluntary exchange. Speculative markets do a remarkable job of aggregating information; in every head-to-head field comparison made so far, their forecasts have been at least as accurate as those of competing institutions, such as official government estimates. Many organizations are now trying to take advantage of this effect, experimenting with the creation of "prediction markets" or "information markets," to forecast future events such as product sales and project completion dates. This chapter examines the uses and limitations of decision markets. Decision markets are information markets designed to inform a particular policy decision, by directly estimating relevant consequences of that decision. After reviewing the weaknesses of existing institutions, the mechanics of decision markets, and a concrete example, this chapter reviews the requirements, advantages, and disadvantages of decision markets. The chapter also takes a close look at a particular application of this tool: the controversial yet illuminating attempt to establish a "Policy Analysis Market" to forecast the consequences of major policy U.S. choices in the Middle East.

Interpreting the Predictions of Prediction Markets

Participants in prediction markets such as the Iowa Electronic Markets trade all-or-nothing contracts that pay a dollar if and only if specified future events occur. Researchers engaged in empirical study of prediction markets have argued broadly that equilibrium prices of the contracts traded are market probabilities' that the specified events will occur. This paper shows that if traders are risk-neutral price takers with heterogenous beliefs, the price of a contract in a prediction market reveals nothing about the dispersion of traders' beliefs and partially identifies the central tendency of beliefs. Most persons have beliefs higher than price when price is above 0.5, and most have beliefs lower than price when price is below 0.5. The mean belief of traders lies in an interval whose midpoint is the equilibrium price. These findings persist even if traders use price data to revise their beliefs in plausible ways.

Prediction Markets in Theory and Practice

Prediction Markets, sometimes referred to as "information markets," "idea futures" or "event futures", are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market-aggregated forecasts. This article summarizes the recent literature on prediction markets, highlighting both theoretical contributions that emphasize the possibility that these markets efficiently aggregate disperse information, and the lessons from empirical applications which show that market-generated forecasts typically outperform most moderately sophisticated benchmarks. Along the way, we highlight areas ripe for future research.

Information (In)Efficiency in Prediction Markets

We analyze the extent to which simple markets can be used to aggregate dispersed information into efficient forecasts of unknown future events. From the examination of case studies in a variety of financial settings we enumerate and suggest solutions to various pitfalls of these simple markets. Despite the potential problems, we show that market-generated forecasts are typically fairly accurate in a variety of prediction contexts, and that they outperform most moderately sophisticated benchmarks. We also show how conditional contracts can be used to discover the markets belief about correlations between events, and how with further assumptions these correlations can be used to make decisions

Profiling a decade of information systems frontiers’ research

This article analyses the first ten years of research published in the Information Systems Frontiers (ISF) from 1999 to 2008. The analysis of the published material includes examining variables such as most productive authors, citation analysis, universities associated with the most publications, geographic diversity, authors’ backgrounds and research methods. The keyword analysis suggests that ISF research has evolved from establishing concepts and domain of information systems (IS), technology and management to contemporary issues such as outsourcing, web services and security. The analysis presented in this paper has identified intellectually significant studies that have contributed to the development and accumulation of intellectual wealth of ISF. The analysis has also identified authors published in other journals whose work largely shaped and guided the researchers published in ISF. This research has implications for researchers, journal editors, and research institutions

A Primer on Information Markets

In 1988 the US Commodity Futures Trading Commission gave permission for the University of Iowa to begin operating the Iowa Electronic Market (IEM) thus ushering in the world's first information market (sometimes called a prediction market). Similar markets have subsequently appeared at the University of British Columbia and Vienna University of Technology. Outside the education sector firms such as Trade Exchange Network (tradesports.com) and a joint venture between Goldman Sachs and Deutsche Bank (economicderivatives.com) have set up public information markets while other firms such as Hewlett-Packard Lilly and Siemens have used information markets for internal purposes. Information markets are similar to standard derivatives markets in that they provide a mechanism for trading financial claims to future contingencies. However they differ in that first they are more accessible to small investors and second they offer markets on a wider range of events including politics sports legal weather business and entertainment. The increasing popularity of information markets reflects several factors. The university-based markets were initially designed to serve primarily as teaching and research tools by providing students and staff with the opportunity to study a trading environment that is more realistic than the typical laboratory setting but without the scale complexity and noise of real-world markets. More recently based on the proven ability of markets to gather and assimilate dispersed information the potential forecasting power of information markets has generated most interest.In this paper we describe the structure of some existing information marketsoutline their key features explain what they can be used for and assess theirpredictive ability. Finally we consider the possible advantages of setting up of an information market in New Zealand

Five Open Questions About Prediction Markets

Interest in prediction markets has increased in the last decade, driven in part by the hope that these markets will prove to be valuable tools in forecasting, decision-making and risk management -- in both the public and private sectors. This paper outlines five open questions in the literature, and we argue that resolving these questions is crucial to determining whether current optimism about prediction markets will be realized.