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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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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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  • Ali M (1977) Probability and utility estimates for racetrack bettors. J Polit Econ 85:803–815

    Article  Google Scholar 

  • Griffith RM (1949) Odds adjustments by American horse race bettors. Am J Psychol 62:290–294

    Article  Google Scholar 

  • Hausch DB, Lo VSY, Ziemba T (2008) Efficiency of racetrack betting markets, 2008 edn. World Scientific, Singapore

    Book  Google Scholar 

  • Hill B, Lane D, Sudderth W (1980) A strong law for some generalized urn processes. Ann Prob 8:214–226

    Article  Google Scholar 

  • Hisakado M, Mori S (2010) Phase transition and information cascade in voting model. J Phys A Math Theor 43:315207–315219

    Article  Google Scholar 

  • Hisakado M, Mori S (2011) Digital herders and phase transition in a voting model. J Phys A Math Theor 44:275204–275220

    Article  Google Scholar 

  • Ichinomiya T (2006) Power-law distribution in Japanese racetrack betting. Physica A 368:207–214

    Article  Google Scholar 

  • Manski C (2006) Interpreting the predictions of prediction markets. Econ Lett 91:425–429

    Article  Google Scholar 

  • Mori S, Hisakado M (2009) Emergence of scale invariance and efficiency in racetrack betting market. In: Matsushita M, Aruka Y, Namatame A, Sato H (eds) Proceedings of the 9th Asia-Pacific complex systems conference complex 09, pp 258–267. Available via arXiv

  • Mori S, Hisakado M (2010) Exact scale invariance in mixing of binary candidates in voting model. J Phys Soc Jpn 79:034001–034008

    Article  Google Scholar 

  • Mori S, Hisakado M (2015) Correlation function for generalized Pólya urns: finite-size scaling analysis. Phys Rev E92:052112–052121

    Google Scholar 

  • Park K, Dommany E (2001) Power law distribution of dividends in horse races. Europhys Lett 53:419–425

    Article  Google Scholar 

  • Wolfers J, Zitzewitz E (2004) Prediction markets. J Econ Persp 18:107–126

    Article  Google Scholar 

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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.

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