In practice, scoring rules elicit good probability estimates from individuals, while betting markets elicit good consensus estimates from groups. Market scoring rules combine these features, eliciting estimates from individuals or groups, with groups costing no more than individuals.

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.

Game sites on the World Wide Web draw people from around the world with specialized interests, skills, and knowledge.

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.

In this paper we study the problem of centrally organizing a market where the participants submit bids for contingent claims over the outcome of a future event and the market organizer must determine which bids to accept. The bidder will select a set of future states and a price at which he is willing to buy the contingent claims. By accepting a bid, the market organizer agrees to pay the bidder a fixed amount if one of the bidder’s selected states is realized. We will specifically study markets which are run as call auctions where the organizer holds the auction open until a certain time and then determines the bids to accept and reject. This type of market has broad usage in financial markets, betting markets and general prediction markets. Lange and Economides [8] have developed a parimutuel mechanism for solving such a market with many positive characteristics. However, one drawback of their formulation is that their mathematical model is not convex and no efficient algorithm is known to solve it. In this paper, we introduce a new mathematical formulation called the Convex Parimutuel Call Auction Mechanism (CPCAM). This formulation produces many of the same advantageous properties of the Lange and Economides model but can more easily be solved due to its convexity. In particular, our model yields the first fully polynomial–time approximation scheme (FPTAS) for the problem. Moreover, we show that our model actually produces identical state prices as the Lange and Economides model. As a corollary, we show that by first obtaining the state prices from our model, the Lange and Economides model becomes a linear program and hence can be solved in polynomial time.

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.

Information Aggregation Mechanisms (IAMs) based on parimutuel-type betting systems can aggregate information from complex environments. However, the performance of previously studied systems leaves something to be desired due to possible bluffing, strategic timing of decisions and a so called long shot bias. This paper demonstrates that two modifications of parimutuel systems improve information aggregation performance by removing disinformation due to strategic behavior and by removing misleading disequilibrium behavior. The experiments also demonstrate that the so called long shot bias results from disequilibrium behavior as opposed to having roots in the psychology of the individuals. Design Improved Parimutuel-type Information

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1 Introduction and description of election futures markets The Iowa Electronic Markets are small-scale, 1 real-money futures markets conducted by the University of Iowa Henry B. Tippie College of Business. In this review, we focus on the best known of these markets, The Iowa Political Markets. 2 Contracts in these markets are designed so that prices should predict election outcomes. The

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.