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KellyBoost: Growth-Optimal Portfolio Construction with Gradient-Boosted Trees

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  • Jiayu Li

Abstract

KellyBoost is a single multi-output XGBoost model whose softmax output is the portfolio: with y the vector of per-asset holding-period returns, the training loss is - log(1 + w y), the negative log growth rate, so the fitted model is the growth-optimal (Kelly) allocation conditioned on the features. The objective is exact rather than a surrogate: we derive the gradient, the analytic diagonal Hessian and the full Hessian in closed form, verify them by finite differences, and ship a dependency-free reference engine.

Suggested Citation

  • Jiayu Li, 2026. "KellyBoost: Growth-Optimal Portfolio Construction with Gradient-Boosted Trees," Papers 2608.23393, arXiv.org.
    • Handle: RePEc:arx:papers:2608.23393
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    File URL: https://arxiv.org/pdf/2608.23393
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