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Generalized framework for applying the Kelly criterion to stock markets

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  • Tim Byrnes
  • Tristan Barnett

Abstract

We develop a general framework for applying the Kelly criterion to stock markets. By supplying an arbitrary probability distribution modeling the future price movement of a set of stocks, the Kelly fraction for investing each stock can be calculated by inverting a matrix involving only first and second moments. The framework works for one or a portfolio of stocks and the Kelly fractions can be efficiently calculated. For a simple model of geometric Brownian motion of a single stock we show that our calculated Kelly fraction agrees with existing results. We demonstrate that the Kelly fractions can be calculated easily for other types of probabilities such as the Gaussian distribution and correlated multivariate assets.

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  • Tim Byrnes & Tristan Barnett, 2018. "Generalized framework for applying the Kelly criterion to stock markets," Papers 1806.05293, arXiv.org.
    • Handle: RePEc:arx:papers:1806.05293
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    Cited by:

    1. Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi, 2024. "Quantifying neural network uncertainty under volatility clustering," Papers 2402.14476, arXiv.org, revised Sep 2024.
    2. Vuko Vukcevic & Robert Keser, 2024. "Sizing the bets in a focused portfolio," Papers 2402.15588, arXiv.org.

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