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How Betters Vote in Horse Race Betting Market

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Applications of Data-Centric Science to Social Design

Part of the book series: Agent-Based Social Systems ((ABSS,volume 14))

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Abstract

Racetrack betting market is famous for its efficiency. The winning probability of a win betting is equal with its vote share, and the discrepancy is negligibly small. Furthermore, the accuracy of the predictions of the market participants is remarkable. Nowadays machine learning has developed much; it cannot exceed the predictions of the markets. In this chapter, we review the accuracy and efficiency of the market using JRA (Japan Racing Association) 1986–2008 win betting data. Then we study the time series data of the betting in 2008 JRA win betting market. We study how the efficiency and the accuracy improve as betting proceeds. We derive the response function of the betters and interpret it as the combination of arbitrager, independent (noisy) voter and herder.

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Mori, S., Hisakado, M. (2019). How Betters Vote in Horse Race Betting Market. In: Sato, AH. (eds) Applications of Data-Centric Science to Social Design. Agent-Based Social Systems, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-10-7194-2_13

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