Abstract: Building on the success of prediction markets at forecasting political elections and other matters of public interest, firms have made increasing use of prediction markets to help make business decisions. This Article explores the implications of prediction markets for corporate governance. Prediction markets can increase the flow of information, encourage truth telling by internal and external firm monitors, and create incentives for agents to act in the interest of their principals. The markets can thus serve as potentially efficient alternatives to other approaches to providing information, such as the Sarbanes-Oxley Act’s internal controls provisions. Prediction markets can also produce an avenue for insiders to profit on and thus reveal inside information while maintaining a level playing field in the market for a firm’s securities. This creates a harmless way around existing insider trading laws, undercutting the argument for the repeal of these laws. In addition, prediction markets can reduce agency costs by providing direct assessments of corporate policies, thus serving as an alternative or complement to shareholder voting as a means of disciplining corporate boards and managers. Prediction markets may thus be particularly useful for issues where agency costs are greatest, such as executive compensation. Deployment of these markets, whether voluntarily or perhaps someday as a result of legal mandates, could improve alignment between shareholders and managers on these issues better than other proposed reforms. These markets might also displace the business judgment rule because they can furnish contemporaneous and relatively objective benchmarks for courts to evaluate business decisions.

Click here to download the full version of the paper.

Abstract: Developing obtainable, clear and measurable work expectations early in the project planning process is an important part of successful project management. Converting these expectations into project milestones and communicating openly about progress toward them is crucial to every project’s success. Optimistic estimation biases of IT workers, poor estimating techniques and group politics can hinder communication and decrease the chances of success. A prediction market is a tool that might help project managers overcome these obstacles.

Prediction markets are online marketplaces that adapt many of the same structures found in stock markets to aggregate information about the probability of future events. These markets have produced reliable estimates in a variety of settings, including corporate environments. This presentation will describe the design, implementation and evaluation of a prediction market to support the communication needs of an IT project manager overseeing the implementation of a software system in a distributed team environment.

Click here to download the full version of the paper.

Abstract: In this paper, we examine the relative forecast accuracy of information markets versus expert aggregation. We lever- age a unique data source of almost 2000 people’s subjective probability judgments on 2003 US National Football League games and compare with the “market probabilities” given by two different information markets on exactly the same events. We combine assessments of multiple experts via linear and logarithmic aggregation functions to form pooled predictions. Prices in information markets are used to derive market predictions. Our results show that, at the same time point ahead of the game, information markets provide as accurate predictions as pooled expert assessments. In screening pooled expert predictions, we find that arithmetic average is a robust and efficient pooling function; weighting expert assessments according to their past performance does not improve accuracy of pooled predictions; and logarithmic aggregation functions offer bolder predictions than linear aggregation functions. The results provide insights into the predictive performance of information markets, and the relative merits of selecting among various opinion pooling methods.

Click here to download the full version of the paper.