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The Kelly Criterion in Blackjack Sports Betting, and the Stock Market

In: THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE

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  • Edward O. Thorp

Abstract

The central problem for gamblers is to find positive expectation bets. But the gambler also needs to know how to manage his money, i.e., how much to bet. In the stock market (more inclusively, the securities markets) the problem is similar but more complex. The gambler, who is now an “investor”, looks for “excess risk adjusted return”. In both these settings, we explore the use of the Kelly criterion, which is to maximize the expected value of the logarithm of wealth (“maximize expected logarithmic utility”). The criterion is known to economists and financial theorists by names such as the “geometric mean maximizing portfolio strategy”, maximizing logarithmic utility, the growth-optimal strategy, the capital growth criterion, etc. The author initiated the practical application of the Kelly criterion by using it for card counting in blackjack. We will present some useful formulas and methods to answer various natural questions about it that arise in blackjack and other gambling games. Then we illustrate its recent use in a successful casino sports betting system. Finally, we discuss its application to the securities markets where it has helped the author to make a thirty year total of 80 billion dollars worth of “bets”.

Suggested Citation

  • Edward O. Thorp, 2011. "The Kelly Criterion in Blackjack Sports Betting, and the Stock Market," World Scientific Book Chapters, in: Leonard C MacLean & Edward O Thorp & William T Ziemba (ed.), THE KELLY CAPITAL GROWTH INVESTMENT CRITERION THEORY and PRACTICE, chapter 54, pages 789-832, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789814293501_0054
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    Citations

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    Cited by:

    1. Chung-Han Hsieh, 2020. "Generalization of Affine Feedback Stock Trading Results to Include Stop-Loss Orders," Papers 2004.12848, arXiv.org.
    2. David J Johnstone, 2023. "Capital budgeting and Kelly betting," Australian Journal of Management, Australian School of Business, vol. 48(3), pages 625-651, August.
    3. G. Bottazzi & D. Giachini, 2019. "Far from the madding crowd: collective wisdom in prediction markets," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1461-1471, September.
    4. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos & Verousis, Thanos, 2020. "A conditional fuzzy inference approach in forecasting," European Journal of Operational Research, Elsevier, vol. 283(1), pages 196-216.
    5. Mu-En Wu & Jia-Hao Syu & Chien-Ming Chen, 2022. "Kelly-Based Options Trading Strategies on Settlement Date via Supervised Learning Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1627-1644, April.
    6. Ziemba, William, 2016. "A response to Professor Paul A. Samuelson's objections to Kelly capital growth investing," LSE Research Online Documents on Economics 119002, London School of Economics and Political Science, LSE Library.
    7. Ye-Sheen Lim & Denise Gorse, 2020. "Deep Probabilistic Modelling of Price Movements for High-Frequency Trading," Papers 2004.01498, arXiv.org.
    8. Stefanos Bennett & Mihai Cucuringu & Gesine Reinert, 2022. "Lead-lag detection and network clustering for multivariate time series with an application to the US equity market," Papers 2201.08283, arXiv.org.

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