# On Kelly Betting: Some Limitations

arXiv: https://arxiv.org/abs/1710.01787 · HTML: https://mlsanity.com/paper/1710.01787/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Oct 2017.

## Built on by (most cited first, 1 of 1)

- [Machine learning for sports betting: should model selection be based on accuracy or calibration?](https://mlsanity.com/paper/2303.06021/) (2023)

## Abstract (arXiv)

The focal point of this paper is the so-called Kelly Criterion, a prescription for optimal resource allocation among a set of gambles which are repeated over time. The criterion calls for maximization of the expected value of the logarithmic growth of wealth. While significant literature exists providing the rationale for such an optimization, this paper concentrates on the limitations of the Kelly-based theory. To this end, we fill a void in published results by providing specific examples quantifying what difficulties are encountered when Taylor-style approximations are used and when wealth drawdowns are considered. For the case of drawdown, we describe some research directions which we feel are promising for improvement of the theory.