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Multi-period Trading Prediction Markets with Connections to Machine Learning

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http://jmlr.org/proceedings/papers/v32/hu14.html
Original languageEnglish
Title of host publicationProceedings of ICML 2014
PublisherJournal of Machine Learning Research: Workshop and Conference Proceedings
Pages1773-1781
Number of pages9
Volume32
Publication statusPublished - 2014

Abstract

We present a new model for prediction markets, in which we use risk measures to model agents and introduce a market maker to describe the trading process. This specific choice on modelling tools brings us mathematical convenience. The analysis shows that the whole market effectively approaches a global objective, despite that the market is designed such that each agent only cares about its own goal. Additionally, the market dynamics provides a sensible algorithm for optimising the global objective. An intimate connection between machine learning and our markets is thus established, such that we could 1) analyse a market by applying machine learning methods to the global objective, and 2) solve machine learning problems by setting up and running certain markets.

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