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Hanson's Automated Market Maker

Author

Listed:
  • Henry Berg
  • Todd A. Proebsting

Abstract

From Hanson's “market scoring rule,” we derive all the necessary formulae to implement a corresponding automated market maker for a prediction market. The market maker has many desirable qualities and always stands ready to trade, thus providing liquidity to markets. The formulae cover all transactions for buying and selling market contracts. In addition, we address practical concerns like how to correctly treat rounding errors and how to prevent errors that allow traders to cheat the market, and provide a practical numerical example. We have used Hanson's automated market maker to run many markets at Microsoft.

Suggested Citation

  • 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.
    • Handle: RePEc:buc:jpredm:v:3:y:2009:i:1:p:45-59
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    Citations

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    Cited by:

    1. Strijbis, Oliver & Arnesen, Sveinung, 2019. "Explaining variance in the accuracy of prediction markets," International Journal of Forecasting, Elsevier, vol. 35(1), pages 408-419.
    2. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    3. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    4. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.
    5. Ivo Blohm & Christoph Riedl & Johann Fuller & Orhan Koroglu & Jan Marco Leimeister & Helmut Krcmar, 2012. "The Effects of Prediction Market Design and Price Elasticity on Trading Performance of Users: An Experimental Analysis," Papers 1204.3457, arXiv.org.
    6. Hamed Amini & Maxim Bichuch & Zachary Feinstein, 2023. "Decentralized Prediction Markets and Sports Books," Papers 2307.08768, arXiv.org, revised May 2024.
    7. Pankaj Pandey & Einar Snekkenes, 2016. "Using Financial Instruments to Transfer the Information Security Risks," Future Internet, MDPI, vol. 8(2), pages 1-62, May.
    8. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    9. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.

    More about this item

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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