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A tractable combinatorial market maker using constraint generation

Miroslav Dudik, Sebastien Lahaie, David M. Pennock
2012 Proceedings of the 13th ACM Conference on Electronic Commerce - EC '12  
Our market maker, based on convex optimization and constraint generation, is tractable like independent securities yet propagates some information among related securities like a combinatorial market maker  ...  We present a new automated market maker for providing liquidity across multiple logically interrelated securities.  ...  CONCLUSIONS In this work we presented an automated market maker based on convex optimization and constraint generation that lies between independent markets and a full combinatorial market.  ... 
doi:10.1145/2229012.2229047 dblp:conf/sigecom/DudikLP12 fatcat:62j4ioutlfh7xfhzw4nu4fbr3a

Designing Markets for Prediction

Yiling Chen, David M. Pennock
2010 The AI Magazine  
We survey the literature on prediction mechanisms, including prediction markets and peer prediction systems.  ...  LMSR pricing in this context is tractable using dynamic programming, though slight generalizations of the betting language render it hard (Guo and Pennock 2009 ).  ...  Combinatorial bids are useful in any market but they are almost necessary when the outcome space is itself combinatorial, for example, all possible permutations of a horse race.  ... 
doi:10.1609/aimag.v31i4.2313 fatcat:53kpobhmw5fd3man2ta4dpzv7y

Arbitrage-Free Combinatorial Market Making via Integer Programming

Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan
2016 Proceedings of the 2016 ACM Conference on Economics and Computation - EC '16  
We present a new combinatorial market maker that operates arbitrage-free combinatorial prediction markets specified by integer programs.  ...  At the crux of our method is the Frank-Wolfe (conditional gradient) algorithm which is used to implement a Bregman projection aligned with the market maker's cost function, using an IP solver as an oracle  ...  By using three different seeds for the randomization, we generated three input files for the market engine. All market makers were run on all three input files.  ... 
doi:10.1145/2940716.2940767 dblp:conf/sigecom/KroerDLB16 fatcat:qgyzdg2ohreknl4npukd2tsaf4

An optimization-based framework for automated market-making

Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
2011 Proceedings of the 12th ACM conference on Electronic commerce - EC '11  
We propose a general framework for the design of securities markets over combinatorial or infinite state or outcome spaces.  ...  We also show that by relaxing the convex hull we can gain computational tractability without compromising the market institution's bounded budget.  ...  ACKNOWLEDGEMENTS This material is based upon work supported by NSF under CNS-0937060 to the CRA for the CIFellows Project, CCF-0953516, NSF grant DMS-070706, DARPA grant FA8750-05-2-0249, and a Yahoo!  ... 
doi:10.1145/1993574.1993621 dblp:conf/sigecom/AbernethyCV11 fatcat:af7qptjd3rhjjag6m5xivuewgm

Graphical Model Market Maker for Combinatorial Prediction Markets

Kathryn Blackmond Laskey, Wei Sun, Robin Hanson, Charles Twardy, Shou Matsumoto, Brandon Goldfedder
2018 The Journal of Artificial Intelligence Research  
We describe algorithms for use by prediction markets in forming a crowd consensus joint probability distribution over thousands of related events.  ...  A combinatorial prediction market forms a consensus joint distribution over many related events by allowing conditional trades or trades on Boolean combinations of events.  ...  The authors thank the anonymous reviewers for thoughtful comments that have helped us to strengthen the paper.  ... 
doi:10.1613/jair.1.11249 fatcat:gqrwaphqcfb23nnfmguiocq77q

Side constraints and non-price attributes in markets

Tuomas Sandholm, Subhash Suri
2006 Games and Economic Behavior  
This is surprising since, as we show, even combinatorial markets with a host of very similar side constraints can be cleared in polytime.  ...  An extreme equality constraint makes combinatorial markets polytime clearable even if bids have to be accepted entirely or not at all.  ...  We then run the winner determination in the (combinatorial) market using prices Ô ¼ .  ... 
doi:10.1016/j.geb.2005.06.001 fatcat:havwzqtuyrh2hm5j2zclwcmgcm

Learning Parameters by Prediction Markets and Kelly Rule for Graphical Models

Wei Sun, Robin Hanson, Kathryn B. Laskey, Charles Twardy
2013 Conference on Uncertainty in Artificial Intelligence  
In this paper we create a Kelly rule automated trader for combinatorial prediction markets and evaluate its performance by numerical simulation.  ...  Agents in a prediction market trade on futures in events of interest. Their trades collectively determine a probability distribution.  ...  over a set of variables for which there is a continuous combinatorial market maker.  ... 
dblp:conf/uai/Sun13 fatcat:gofvl34wnjahxkc7b7ni3xujuu

Efficient Market Making via Convex Optimization, and a Connection to Online Learning

Jacob Abernethy, Yiling Chen, Jennifer Wortman Vaughan
2013 ACM Transactions on Economics and Computation  
We propose a general framework for the design of securities markets over combinatorial or infinite state or outcome spaces.  ...  Using our framework, we illustrate the mathematical parallels between cost function based markets and online learning and establish a correspondence between cost function based markets and market scoring  ...  In general, this type of ad hoc reasoning can lead us to many apparently reasonable constraints, but does not yield an algorithm to determine whether or not we have generated the full set of constraints  ... 
doi:10.1145/2465769.2465777 fatcat:b5jgmbb42rbv7mi7jzneee7a6q

What-If Analysis Through Simulation-Optimization Hybrids

Marco Gavanelli, Michela Milano, Alan Holland, Barry O'Sullivan
2012 ECMS 2012 Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann  
When a simulator is available, a human expert, e.g., a policy maker, might understand the impact of her choices by running a simulator on a set of scenarios of interest.  ...  In this paper we propose and experiment with one approach for combining simulation with a combinatorial optimization and decision making component.  ...  The European Commission is not liable for any use that may be made of the information contained in this paper.  ... 
doi:10.7148/2012-0624-0630 dblp:conf/ecms/GavanelliMHO12 fatcat:mp22htoctnhppicmeyyx26573m

Recent advances in robust optimization: An overview

Virginie Gabrel, Cécile Murat, Aurélie Thiele
2014 European Journal of Operational Research  
It seeks to give a representative picture of the research topics most explored in recent years, highlight common themes in the investigations of independent research teams and highlight the contributions  ...  With respect to the practice of robust optimization, we consider a broad spectrum of applications, in particular inventory and logistics, finance, revenue management, but also queueing networks, machine  ...  They solve a robust ranking problem using a constraint generation scheme.  ... 
doi:10.1016/j.ejor.2013.09.036 fatcat:negoppbbu5hanjkdlccdwjb35a

Mathematical foundations for social computing

Yiling Chen, Arpita Ghosh, Michael Kearns, Tim Roughgarden, Jennifer Wortman Vaughan
2016 Communications of the ACM  
The term social computing is often used as a synonym for several related areas, such as "human computation" and subsets of "collective intelligence;" we use it in its broadest sense to encompass all of  ...  projects, and collaboratively edited wikis, to name a few.  ...  kets using an automated market maker called a market scoring rule.  ... 
doi:10.1145/2960403 fatcat:s6deqdwnwvb4rpds3n346yx5ge

Combinatorial auctions

Jawad Abrache, Teodor Gabriel Crainic, Michel Gendreau, Monia Rekik
2007 Annals of Operations Research  
Combinatorial auctions are an important class of market mechanisms in which participants are allowed to bid on bundles of multiple heterogeneous items.  ...  In this paper, we discuss several complex issues that are encountered in the design of combinatorial auctions.  ...  A comprehensive compilation of generic classes of side constraints for combinatorial markets, and examination of their impacts on the complexity of winner determination formulations can be found in .  ... 
doi:10.1007/s10479-007-0179-z fatcat:dt2oav6acjesjcdfbqz3526dqa

Betting on the Real Line [chapter]

Xi Gao, Yiling Chen, David M. Pennock
2009 Lecture Notes in Computer Science  
Both the call market mechanism and two automated market maker mechanisms, logarithmic market scoring rule (LMSR) and dynamic parimutuel markets (DPM), are generalized to handle interval bets on continuous  ...  The LMSR market maker suffers from unbounded loss for both countably infinite and continuous outcomes.  ...  In practice, an infinite-outcome DPM market maker can start with a quantity vector that has only finite positive elements and all others are zeros, or use an infinite converging series.  ... 
doi:10.1007/978-3-642-10841-9_55 fatcat:2acb7757t5aa7n2yp2wtnzkzuq

Theory and Applications of Robust Optimization [article]

Dimitris Bertsimas and David B. Brown and Constantine Caramanis
2010 arXiv   pre-print
Finally, we highlight applications of RO across a wide spectrum of domains, including finance, statistics, learning, and various areas of engineering.  ...  130] compute robust "efficient frontiers" using real-world market data.  ...  We give a summary of the main issues raised, and results presented. 1. Tractability: In general, the robust version of a tractable 1 optimization problem may not itself be tractable.  ... 
arXiv:1010.5445v1 fatcat:dla2klcm4rdhhoqa72hakbwuqe

Theory and Applications of Robust Optimization

Dimitris Bertsimas, David B. Brown, Constantine Caramanis
2011 SIAM Review  
Finally, we highlight applications of RO across a wide spectrum of domains, including finance, statistics, learning, and various areas of engineering. ). 1 Throughout this paper, we use the term "tractable  ...  Our goal here is to provide a more condensed, higher-level summary of key methodological results as well as a broad array of applications that use RO. A First Example.  ...  We give a summary of the main issues raised and results presented. 1. Tractability. In general, the robust version of a tractable 1 optimization problem may not itself be tractable.  ... 
doi:10.1137/080734510 fatcat:aph3746da5c7noab5feoyxyyba
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