Combinatorial Information Market Design
Information Systems Frontiers
Convex Optimization
Prediction, Learning, and Games
Prediction, Learning, and Games
Proceedings of the 8th ACM conference on Electronic commerce
Pricing combinatorial markets for tournaments
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Complexity of combinatorial market makers
Proceedings of the 9th ACM conference on Electronic commerce
The effects of market-making on price dynamics
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Parimutuel Betting on Permutations
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Combinatorial prediction markets for event hierarchies
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Pari-mutuel markets: mechanisms and performance
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
A new understanding of prediction markets via no-regret learning
Proceedings of the 11th ACM conference on Electronic commerce
A practical liquidity-sensitive automated market maker
Proceedings of the 11th ACM conference on Electronic commerce
A Unified Framework for Dynamic Prediction Market Design
Operations Research
Liquidity-sensitive automated market makers via homogeneous risk measures
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
A tractable combinatorial market maker using constraint generation
Proceedings of the 13th ACM Conference on Electronic Commerce
Proceedings of the 13th ACM Conference on Electronic Commerce
Efficient Market Making via Convex Optimization, and a Connection to Online Learning
ACM Transactions on Economics and Computation - Special Issue on Algorithmic Game Theory
An axiomatic characterization of adaptive-liquidity market makers
Proceedings of the fourteenth ACM conference on Electronic commerce
A combinatorial prediction market for the U.S. elections
Proceedings of the fourteenth ACM conference on Electronic commerce
Cost function market makers for measurable spaces
Proceedings of the fourteenth ACM conference on Electronic commerce
An introduction to artificial prediction markets for classification
The Journal of Machine Learning Research
A Practical Liquidity-Sensitive Automated Market Maker
ACM Transactions on Economics and Computation
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We propose a general framework for the design of securities markets over combinatorial or infinite state or outcome spaces. The framework enables the design of computationally efficient markets tailored to an arbitrary, yet relatively small, space of securities with bounded payoff. We prove that any market satisfying a set of intuitive conditions must price securities via a convex cost function, which is constructed via conjugate duality. Rather than deal with an exponentially large or infinite outcome space directly, our framework only requires optimization over a convex hull. By reducing the problem of automated market making to convex optimization, where many efficient algorithms exist, we arrive at a range of new polynomial-time pricing mechanisms for various problems. We demonstrate the advantages of this framework with the design of some particular markets. We also show that by relaxing the convex hull we can gain computational tractability without compromising the market institution's bounded budget.