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The problem of market clearing is to set a price for an item such that quantity demanded equals quantity supplied. In this work, we cast the problem of predicting clearing prices into a learning framework and use the resulting models to…

Machine Learning · Computer Science 2019-06-25 Weiran Shen , Sébastien Lahaie , Renato Paes Leme

An asymmetric information model is introduced for the situation in which there is a small agent who is more susceptible to the flow of information in the market than the general market participant, and who tries to implement strategies…

Trading and Market Microstructure · Quantitative Finance 2013-01-31 Dorje C. Brody , Mark H. A. Davis , Robyn L. Friedman , Lane P. Hughston

There is a class of models for pol/mil/econ bargaining and conflict that is loosely based on the Median Voter Theorem which has been used with great success for about 30 years. However, there are fundamental mathematical limitations to…

Computer Science and Game Theory · Computer Science 2015-05-12 Ben Wise , Steven Bankes

Decisions taken in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market therefore provides a rich environment to study how people take…

General Finance · Quantitative Finance 2016-09-28 Mario Gutiérrez-Roig , Carlota Segura , Jordi Duch , Josep Perelló

We analyse strategic, complete information, sequential voting with ordinal preferences over the alternatives. We consider several voting mechanisms: plurality voting and approval voting with deterministic or uniform tie-breaking rules. We…

Computer Science and Game Theory · Computer Science 2019-04-19 Oren Dean , Yakov Babichenko , Moshe Tennenholtz

Elections where electors rank the candidates (or a subset of the candidates) in order of preference allow the collection of more information about the electors' intent. The most widely used election of this type is Instant-Runoff Voting…

Computers and Society · Computer Science 2023-12-06 Michelle Blom , Peter J. Stuckey , Vanessa Teague , Damjan Vukcevic

Prediction markets are widely treated as forecasting devices that reveal collective expectations about uncertain futures. This article argues that under specifiable conditions they also function as coordination mechanisms: public…

General Economics · Economics 2026-04-29 Maksym Nechepurenko

We consider the problem of belief aggregation: given a group of individual agents with probabilistic beliefs over a set of uncertain events, formulate a sensible consensus or aggregate probability distribution over these events. Researchers…

Artificial Intelligence · Computer Science 2013-02-08 David M. Pennock , Michael P. Wellman

We introduce a new class of combinatorial markets in which agents have covering constraints over resources required and are interested in delay minimization. Our market model is applicable to several settings including scheduling, cloud…

Computer Science and Game Theory · Computer Science 2017-04-17 Nikhil Devanur , Jugal Garg , Ruta Mehta , Vijay V. Vazirani , Sadra Yazdanbod

We generalize Condorcet's jury theorem (CJT) to socially connected populations in which agents revise discrete choices on a network in the presence of zealots. Free agents receive privately informative signals about the correct alternative…

Physics and Society · Physics 2025-10-21 Dan Braha , Marcus A. M. de Aguiar

This work is concerned with the dynamics of online cultural markets, namely, attention allocation of many users on a set of digital goods with infinite supply. Such dynamic is important in shaping processes and outcomes in society, from…

Social and Information Networks · Computer Science 2023-04-25 Haiqing Zhu , Yun Kuen Cheung , Lexing Xie

Like many other voting systems, Majority Judgement suffers from the weaknesses of the underlying mathematical model: Elections as problem of choice or ranking. We show how the model can be enhanced to take into account the complete process…

Computer Science and Game Theory · Computer Science 2023-07-07 Friedemann Kemm

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their…

Statistical Mechanics · Physics 2008-12-02 Kay-Yut Chen , Leslie R. Fine , Bernardo A. Huberman

We present theoretical and empirical results demonstrating the usefulness of voting rules for participatory democracies. We first give algorithms which efficiently elicit \epsilon-approximations to two prominent voting rules: the Borda rule…

Multiagent Systems · Computer Science 2014-07-17 David Lee , Ashish Goel , Tanja Aitamurto , Helene Landemore

We study situations where a group of voters need to take a collective decision over a number of public issues, with the goal of getting a result that reflects the voters' opinions in a proportional manner. Our focus is on interconnected…

Computer Science and Game Theory · Computer Science 2025-09-25 Julian Chingoma , Umberto Grandi , Arianna Novaro

We examine probabilistic forecasts for battleground states in the 2020 US presidential election, using daily data from two sources over seven months: a model published by The Economist, and prices from the PredictIt exchange. We find…

General Economics · Economics 2021-05-26 Rajiv Sethi , Julie Seager , Emily Cai , Daniel M. Benjamin , Fred Morstatter

During deliberation processes, mediators and facilitators typically need to select a small and representative set of opinions later used to produce digestible reports for stakeholders. In online deliberation platforms, algorithmic selection…

Computers and Society · Computer Science 2026-02-18 Salim Hafid , Manon Berriche , Jean-Philippe Cointet

We analyze Assessment Voting, a new two-round voting procedure that can be applied to binary decisions in democratic societies. In the first round, a randomly-selected number of citizens cast their vote on one of the two alternatives at…

Econometrics · Economics 2018-02-06 Hans Gersbach , Akaki Mamageishvili , Oriol Tejada

A ranking is an ordered sequence of items, in which an item with higher ranking score is more preferred than the items with lower ranking scores. In many information systems, rankings are widely used to represent the preferences over a set…

Artificial Intelligence · Computer Science 2017-09-22 Zhiwei Lin , Yi Li , Xiaolian Guo

The Artificial Prediction Market is a recent machine learning technique for multi-class classification, inspired from the financial markets. It involves a number of trained market participants that bet on the possible outcomes and are…

Machine Learning · Statistics 2014-08-18 Nathan Lay , Adrian Barbu