I develop a new mechanism for risk allocation and information speculation called a dynamic pari-mutuel market (DPM). A DPM acts as hybrid between a pari-mutuel market and a continuous double auction (CDA), inheriting some of the advantages of both. Like a pari-mutuel market, a DPM offers infinite buy-in liquidity and zero risk for the market institution; like a CDA, a DPM can continuously react to new information, dynamically incorporate information into prices, and allow traders to lock in gains or limit losses by selling prior to event resolution. The trader interface can be designed to mimic the familiar double auction format with bid-ask queues, though with an addition variable called the payoff per share. The DPM price function can be viewed as an automated market maker always offering to sell at some price, and moving the price appropriately according to demand. Since the mechanism is pari-mutuel (i.e., redistributive), it is guaranteed to pay out exactly the amount of money taken in. I explore a number of variations on the basic DPM, analyzing the properties of each, and solving in closed form for their respective price functions.

We develop a framework for trading in compound securities: financial instruments that pay off contingent on the outcomes of arbitrary statements in propositional logic. Buying or selling securities -- which can be thought of as betting on or against a particular future outcome -- allows agents both to hedge risk and to profit (in expectation) on subjective predictions. A compound securities market allows agents to place bets on arbitrary boolean combinations of events, enabling them to more closely achieve their optimal risk exposure, and enabling the market as a whole to more closely achieve the social optimum. The tradeoff for allowing such expressivity is in the complexity of the agents' and auctioneer's optimization problems.

This paper explores the possibility of solving supply chain capacity allocation problems using internal markets among employees of the same company. Unlike earlier forms of transfer pricing, IT now makes it easier for such markets to involve many employees, fine-grained transactions, and frequently varying prices. The paper develops a formal mode of such markets, proves their optimality in a baseline condition, and then analyzes various potential market problems and solutions. Interestingly, these proposed solutions are not possible in a conventional market because they rely on the firm’s ability to pay marke participants based on factors other than just the profitability of their market transactions. For example, internal monopolies can be ameliorated by paying internal monopolists on the basis of corporate, not individual, profits. Incentives for collusion among peers can be reduced by paying participants based on their profits relative to peers. Profit-reducing competition among different sales channels can be reduced by imposing an “internal sales tax”. And problems caused by fixed costs can be avoided by combining “conditional internal markets ” with a “pivot mechanism”.

We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings. A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals' public information. A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants.

Common methods for obtaining and organizing information for evaluating human resource development (HRD) decisions, such as surveys, focus groups, Delphi processes, and discussion at business meetings, can be relatively costly, ad hoc, and difficult to apply. In this article, a review is presented of relatively inexpensive, continuous, and easy-to-apply innovations in information aggregation for examining futures of ideas that are drawn from principles and mechanisms of commodity futures markets. A description is given of how futures markets for ideas have strong applicability to strategic, tactical, and operational decisions about the development, diffusion, and implementation of HRD products and services. Examples are offered for how idea futures markets could support HRD decisions about sales forecasting, product efficacy, project management, environmental scanning, and identification of expertise.

Abstract. In this paper we study the design and characterization of prediction markets in the presence of traders with unknown risk-aversion. We formulate a series of desirable properties for any “market-like ” forecasting mechanism. We present a randomized mechanism that satisfies all these properties while guaranteeing that it is myopically optimal for each trader to trade honestly, regardless of her degree of risk aversion. We observe, however, that the mechanism has an undesirable side effect: the traders ’ expected reward, normalized against the inherent value of their private information, decreases exponentially with the number of traders. We prove that this is unavoidable: any mechanism that is myopically strategyproof for traders of all risk types, while also satisfying other natural properties of “market-like ” mechanisms, must sometimes result in a player getting an exponentially small normalized expected reward. 1 Introduction and Related Work Prediction markets are markets designed and deployed to aggregate information about future events by having agents with private beliefs trade in these markets. One market

Abstract—The concepts and methods used in commodity and financial futures markets are adapted to structure “idea” futures markets. Instead of trading on future prices for commodities or financial instruments, an idea futures market trades on the likelihood of realization of a specific, identifiable, operational proposition at some future point in time—an idea. Shares in an idea future are bought and sold using standard market methods. The price of a future reflects the aggregated information over all traders about the probability associated with the proposition. Prices rise or fall based upon changes in information perceived by market participants. Idea futures markets have strong applicability to strategic, tactical, and logistics decisions about the development, diffusion, and implementation of educational technology products. I.