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32
A utility framework for boundedloss market makers
 In Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence
, 2007
"... We introduce a class of utilitybased market makers that always accept orders at their riskneutral prices. We derive necessary and sufficient conditions for such market makers to have bounded loss. We prove that hyperbolic absolute risk aversion utility market makers are equivalent to weighted pseu ..."
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Cited by 71 (27 self)
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We introduce a class of utilitybased market makers that always accept orders at their riskneutral prices. We derive necessary and sufficient conditions for such market makers to have bounded loss. We prove that hyperbolic absolute risk aversion utility market makers are equivalent to weighted pseudospherical scoring rule market makers. In particular, Hanson’s logarithmic scoring rule market maker corresponds to a negative exponential utility market maker in our framework. We describe a third equivalent formulation based on maintaining a cost function that seems most natural for implementation purposes, and we illustrate how to translate among the three equivalent formulations. We examine the tradeoff between the market’s liquidity and the market maker’s worstcase loss. For a fixed bound on worstcase loss, some market makers exhibit greater liquidity near uniform prices and some exhibit greater liquidity near extreme prices, but no market maker can exhibit uniformly greater liquidity in all regimes. For a fixed minimum liquidity level, we give the lower bound of market maker’s worstcase loss under some regularity conditions. 1
A dynamic parimutuel market for hedging, wagering, and information aggregation
 In Proceedings of the Fifth ACM Conference on Electronic Commerce (EC’04
, 2004
"... I develop a new mechanism for risk allocation and information speculation called a dynamic parimutuel market (DPM). A DPM acts as hybrid between a parimutuel market and a continuous double auction (CDA), inheriting some of the advantages of both. Like a parimutuel market, a DPM offers infinite bu ..."
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Cited by 41 (7 self)
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I develop a new mechanism for risk allocation and information speculation called a dynamic parimutuel market (DPM). A DPM acts as hybrid between a parimutuel market and a continuous double auction (CDA), inheriting some of the advantages of both. Like a parimutuel market, a DPM offers infinite buyin 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 bidask 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 parimutuel (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.
Gaming Prediction Markets: Equilibrium Strategies with a Market Maker
 ALGORITHMICA
, 2008
"... We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that ..."
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Cited by 35 (17 self)
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We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze nonmyopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of riskneutral traders with incomplete information playing in a dynamic game. We consider finitestage and infinitestage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finitestage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting
Betting BooleanStyle: A Framework for Trading in Securities Based on Logical Formulas
, 2003
"... 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 ..."
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Cited by 31 (17 self)
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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.
Computation in a Distributed Information Market
, 2003
"... According to economic theory, supported by empirical and laboratory evidence, the equilibrium price of a financial security reflects all of the information regarding the security's value. We investigate the dynamics of the computational process on the path toward equilibrium, where informatio ..."
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Cited by 24 (5 self)
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According to economic theory, supported by empirical and laboratory evidence, the equilibrium price of a financial security reflects all of the information regarding the security's value. We investigate the dynamics of the computational process on the path toward equilibrium, where information distributed among traders is revealed stepby step over time and incorporated into the market price. We develop a simplified model of an information market, along with trading strategies, in order to formalize the computational properties of the process. We show that securities whose payoffs cannot be expressed as a weighted threshold function of distributed input bits are not guaranteed to converge to the proper equilibrium predicted by economic theory. On the other hand, securities whose payoffs are threshold functions are guaranteed to converge, for all prior probability distributions. Moreover, these threshold securities converge in at most n rounds, where n is the number of bits of distributed information. We also prove a lower bound, showing a type of threshold security that requires at least n/2 rounds to converge in the worst case.
Reading the markets: Forecasting public opinion of political candidates by news analysis
 In Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008
, 2008
"... Media reporting shapes public opinion which can in turn influence events, particularly in political elections, in which candidates both respond to and shape public perception of their campaigns. We use computational linguistics to automatically predict the impact of news on public perception of poli ..."
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Cited by 18 (0 self)
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Media reporting shapes public opinion which can in turn influence events, particularly in political elections, in which candidates both respond to and shape public perception of their campaigns. We use computational linguistics to automatically predict the impact of news on public perception of political candidates. Our system uses daily newspaper articles to predict shifts in public opinion as reflected in prediction markets. We discuss various types of features designed for this problem. The news system improves market prediction over baseline market systems. 1
Bluffing and strategic reticence in prediction markets
 In the third Workshop on Internet and Network Economics
, 2007
"... Abstract. We study the equilibrium behavior of informed traders interacting with two types of automated market makers: market scoring rules (MSR) and dynamic parimutuel markets (DPM). Although both MSR and DPM subsidize trade to encourage information aggregation, and MSR is myopically incentive comp ..."
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Cited by 16 (8 self)
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Abstract. We study the equilibrium behavior of informed traders interacting with two types of automated market makers: market scoring rules (MSR) and dynamic parimutuel markets (DPM). Although both MSR and DPM subsidize trade to encourage information aggregation, and MSR is myopically incentive compatible, neither mechanism is incentive compatible in general. That is, there exist circumstances when traders can benefit by either hiding information (reticence) or lying about information (bluffing). We examine what information structures lead to straightforward play by traders, meaning that traders reveal all of their information truthfully as soon as they are able. Specifically, we analyze the behavior of riskneutral traders with incomplete information playing in a finiteperiod dynamic game. We employ two different information structures for the logarithmic market scoring rule (LMSR): conditionally independent signals and conditionally dependent signals. When signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE) for LMSR. However, when signals are conditionally dependent, there exist joint probability distributions on signals such that at a PBE in LMSR traders have an incentive to bet against their own information—strategically misleading other traders in order to later profit by correcting their errors. In DPM, we show that when traders anticipate sufficiently betterinformed traders entering the market in the future, they have incentive to partially withhold their information by moving the market probability only partway toward their beliefs, or in some cases not participating in the market at all. 1
Decision Markets With Good Incentives
"... Abstract. Decision and prediction markets are designed to determine the likelihood of future events; prediction markets predict what will happen, and decision markets predict the results of a choice, or what would happen. Both allow multiple participants to review and make predictions, and participa ..."
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Cited by 9 (5 self)
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Abstract. Decision and prediction markets are designed to determine the likelihood of future events; prediction markets predict what will happen, and decision markets predict the results of a choice, or what would happen. Both allow multiple participants to review and make predictions, and participants are typically scored for improving the accuracy of the market’s prediction. Previous work has demonstrated prediction markets can reward accuracy improvements, as can a single participant informing a decision. We construct and characterize decision markets where all participants are scored for improving the market’s accuracy. These markets require the decision maker always risk taking an action at random, and reducing this risk increases its potential loss. We also relate these decision markets to sets of prediction markets, demonstrating a correspondence between their perfect Bayesian equilibria. 1
An InDepth Analysis of Information Markets with Aggregate Uncertainty
 ELECTRONIC COMMERCE RESEARCH
, 2006
"... The novel idea of setting up Internetbased virtual markets, information markets, to aggregate dispersed information and predict outcomes of uncertain future events has empirically found its way into many domains. But the theoretical examination of information markets has lagged relative to their ..."
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Cited by 7 (1 self)
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The novel idea of setting up Internetbased virtual markets, information markets, to aggregate dispersed information and predict outcomes of uncertain future events has empirically found its way into many domains. But the theoretical examination of information markets has lagged relative to their implementation and use. This paper proposes a simple theoretical model of information markets to understand their information dynamics. We investigate and provide initial answers to a series of research questions that are important to understanding how information markets work, which are: (1) Does an information market converge to a consensus equilibrium? (2) If yes, how fast is the convergence process? (3) What is the best possible equilibrium of an information market? and (4) Is an information market guaranteed to converge to the best possible equilibrium?
An Empirical Study of Dynamic Parimutuel Markets: Evidence from the Tech Buzz Game
"... Abstract. A dynamic parimutuel market (DPM) is a hybrid between a continuous double auction (CDA) and a parimutuel market. Like a CDA, a DPM incentivizes traders to reveal their information early. Like a parimutuel market, a DPM has infinite liquidity, allowing trades at any time. In this paper, ..."
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Cited by 4 (3 self)
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Abstract. A dynamic parimutuel market (DPM) is a hybrid between a continuous double auction (CDA) and a parimutuel market. Like a CDA, a DPM incentivizes traders to reveal their information early. Like a parimutuel market, a DPM has infinite liquidity, allowing trades at any time. In this paper, we examine empirical questions related to DPMs: Do prices in DPMs predict events of interests? How do traders behave in DPMs? Leveraging a data set from the Yahoo!/O’Reilly Tech Buzz Game, a live system using the DPM, we show that prices offer informative forecasts of future event trends. At the agent level, we find that on average human traders outperform robot traders who randomly place trades. Those human traders who are seemingly more rational, buying when the implied market probability is low and selling when it is high, obtain higher profit on average than those who appear less rational. We examine other aspects of the game, including incentives to manipulate the market. 1