Abstract
In gambling such as horse racing, we are sometimes able to peep peculiar voting behavior by a punter with the advantageous information closely related to the results. The punter is often referred as an insider. In this study, our goal is to propose a reasonable investment strategy by peeping insiders’ decision-making based on the time series odds data in horse racing events held by JRA. We have found the conditions that the rate of return is more than 642 % for races whose winner’s prize money is 20 million yens or more. That suggests the possibility of Knowledge Peeping.
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A type of betting offered by JRA where a punter selects one horse to win.
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Acknowledgements
This work was supported by JSPS KAKENHI Grant Numbers 24300005, 26330081, 26870201. The horse racing data was supplied by Japan Racing Association (JRA). We would like to thank everyone that has helped us.
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Higuchi, S., Orihara, R., Sei, Y., Tahara, Y., Ohsuga, A. (2015). Decision Making Strategy Based on Time Series Data of Voting Behavior. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_20
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DOI: https://doi.org/10.1007/978-3-319-26350-2_20
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