Abstract. A dynamic pari-mutuel market (DPM) is a hybrid between a continuous double auction (CDA) and a pari-mutuel market. Like a CDA, a DPM incentivizes traders to reveal their information early. Like a pari-mutuel 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

An ordered probit regression model estimated using 15 years’ data is used to model English league football match results. As well as past match results data, the significance of the match for end-of-season league outcomes; the involvement of the teams in cup competition; the geographical distance between the two teams ’ home towns; and the average attendances of the two teams all contribute to the model’s performance. The model is used to test the weak-form efficiency of prices in the fixed-odds betting market, and betting strategies with a positive expected return are identified.

I discuss the prospects of opening securities markets in hard computational problems, including satisfiability, counting problems, and Bayesian inference problems. Such NP markets would offer direct monetary incentives for the development of better algorithms. Market prices would serve as collective approximate solutions, and bid-ask spreads may reflect problem difficulty. Some markets offer controlled settings for investigating the speed of information incorporation in markets, and exploring evidence of bounded rationality and imprecise subjective probabilities among market participants. Going once . . . Going twice . . . Sold! Congratulations! You are now the proud owner of . . . . . . one unit of one instance of three-satisfiability problem #V300:C1000:ID854! 1

We propose a model of prediction markets where participants are biased according to their social relationships. We relax the standard assumption of complete rationality and adopt an arguably more realistic model where agents are disproportionally influenced by their neighbors in a social network. We conduct extensive agent-based simulations of our model. We find that prices in prediction markets remain accurate even when participants are biased and irrational. Moreover, accuracy is robust to changes in many factors, including how individuals are motivated to participate in the market, the way that individuals use public information, individual utility functions, the topology of the social network, and the strength of social influences. Our model can explain the high volume of trade often observed in speculative markets that is hard or impossible to explain under standard market rationality assumptions. Our model can also explain the documented ability of prediction markets to succeed even in the face of biased and irrational participants.

Abstract 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 non-myopic strategies and examine what information structures lead to truthful betting by traders. Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage 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 finite-stage 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

We analyze data from 52 online in-game sports betting markets (where betting is allowed continuously throughout a game), including 34 markets based on soccer (European football) games from the 2002 World Cup, and 18 basketball games from the 2002 USA National Basketball Association (NBA) championship. We show that prices on average approach the correct outcome over time, and the price dynamics in the markets are closely coupled with game events, agreeing with efficient market assumptions. We also examine qualitative distinctions between the two types of games.

... In this paper, information markets are introduced as a promising mechanism for predicting uncertain outcomes. Information markets are markets that are specially designed for aggregating information and making predictions on future events. A generic model of information markets is proposed. We derive some fundamental properties on when information markets can converge to the direct communications equilibrium, which aggregates all information across traders and is the best possible prediction for the event under consideration