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Decentralized Prediction Markets and Sports Books

Author

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  • Hamed Amini
  • Maxim Bichuch
  • Zachary Feinstein

Abstract

Prediction markets allow traders to bet on potential future outcomes. These markets exist for weather, political, sports, and economic forecasting. Within this work we consider a decentralized framework for prediction markets using automated market makers (AMMs). Specifically, we construct a liquidity-based AMM structure for prediction markets that, under reasonable axioms on the underlying utility function, satisfy meaningful financial properties on the cost of betting and the resulting pricing oracle. Importantly, we study how liquidity can be pooled or withdrawn from the AMM and the resulting implications to the market behavior. In considering this decentralized framework, we additionally propose financially meaningful fees that can be collected for trading to compensate the liquidity providers for their vital market function.

Suggested Citation

  • Hamed Amini & Maxim Bichuch & Zachary Feinstein, 2023. "Decentralized Prediction Markets and Sports Books," Papers 2307.08768, arXiv.org, revised Jan 2025.
    • Handle: RePEc:arx:papers:2307.08768
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    References listed on IDEAS

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    1. Robin Hanson, 2003. "For Bayesian Wannabes, Are Disagreements Not About Information?," Theory and Decision, Springer, vol. 54(2), pages 105-123, March.
    2. Guillermo Angeris & Tarun Chitra, 2020. "Improved Price Oracles: Constant Function Market Makers," Papers 2003.10001, arXiv.org, revised Jun 2020.
    3. Maxim Bichuch & Zachary Feinstein, 2022. "Axioms for Automated Market Makers: A Mathematical Framework in FinTech and Decentralized Finance," Papers 2210.01227, arXiv.org, revised Feb 2025.
    4. Kalai, Ehud & Lehrer, Ehud, 1993. "Rational Learning Leads to Nash Equilibrium," Econometrica, Econometric Society, vol. 61(5), pages 1019-1045, September.
    5. Guillermo Angeris & Akshay Agrawal & Alex Evans & Tarun Chitra & Stephen Boyd, 2021. "Constant Function Market Makers: Multi-Asset Trades via Convex Optimization," Papers 2107.12484, arXiv.org.
    6. Hanson, Robin, 2002. "Disagreement is unpredictable," Economics Letters, Elsevier, vol. 77(3), pages 365-369, November.
    7. Geanakoplos, John D. & Polemarchakis, Heraklis M., 1982. "We can't disagree forever," Journal of Economic Theory, Elsevier, vol. 28(1), pages 192-200, October.
    8. Monderer, Dov & Samet, Dov, 1989. "Approximating common knowledge with common beliefs," Games and Economic Behavior, Elsevier, vol. 1(2), pages 170-190, June.
    9. Yiling Chen & David M Pennock, 2012. "A Utility Framework for Bounded-Loss Market Makers," Papers 1206.5252, arXiv.org.
    10. Henry Berg & Todd A. Proebsting, 2009. "Hanson's Automated Market Maker," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 45-59, April.
    11. Dai, Min & Jia, Yanwei & Kou, Steven, 2021. "The wisdom of the crowd and prediction markets," Journal of Econometrics, Elsevier, vol. 222(1), pages 561-578.
    12. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    13. Alex Lipton & Artur Sepp, 2021. "Automated Market-Making for Fiat Currencies," Papers 2109.12196, arXiv.org.
    14. Agostino Capponi & Ruizhe Jia, 2021. "The Adoption of Blockchain-based Decentralized Exchanges," Papers 2103.08842, arXiv.org, revised Jul 2021.
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