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Different Measures of Win Rate for Optimal Proportional Betting

Author

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  • Peter A. Griffin

    (Department of Mathematics and Statistics, California State University, Sacramento, California 95819)

Abstract

It is well known that all betting systems applied to independent, repeated, and identically distributed trials will result in the same expected gain per average unit wagered as that which applies to a single trial. This paper develops the asymptotic and paradoxical manner in which that constant win rate is maintained for optimal proportional betting according to the Kelly criterion. The appropriateness of using this traditional measure of win rate for proportional betting is contrasted with that of various alternatives.

Suggested Citation

  • Peter A. Griffin, 1984. "Different Measures of Win Rate for Optimal Proportional Betting," Management Science, INFORMS, vol. 30(12), pages 1540-1547, December.
    • Handle: RePEc:inm:ormnsc:v:30:y:1984:i:12:p:1540-1547
    DOI: 10.1287/mnsc.30.12.1540
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    Cited by:

    1. Rose D. Baker & Ian G. McHale, 2013. "Optimal Betting Under Parameter Uncertainty: Improving the Kelly Criterion," Decision Analysis, INFORMS, vol. 10(3), pages 189-199, September.
    2. Gang Hu & Ming Gu, 2024. "Markowitz Meets Bellman: Knowledge-distilled Reinforcement Learning for Portfolio Management," Papers 2405.05449, arXiv.org.

    More about this item

    Keywords

    betting systems; Kelly criterion;

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