Name
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-26350-2_20 | AI 2015: ADVANCES IN ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Horse racing prediction,Time series data,Optimization,Decision tree,Knowledge peeping | Decision tree,Time series,Actuarial science,Investment strategy,Computer science,Business decision mapping,Insider,Artificial intelligence,Odds,Voting behavior,Machine learning,Rate of return | Conference |
Volume | ISSN | Citations |
9457 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shogo Higuchi | 1 | 0 | 0.34 |
| Ryohei Orihara | 2 | 0 | 0.34 |
| Yuichi Sei | 3 | 12 | 7.26 |
| Yasuyuki Tahara | 4 | 163 | 49.16 |
| Akihiko Ohsuga | 5 | 283 | 73.35 |