How to Gamble If You're In a Hurry

TL;DR

This paper explores the theory of statistical gambling in a discrete, finite setting, using computational methods to analyze strategies and outcomes, contrasting with traditional continuous models.

Contribution

It introduces a discrete, finitistic approach to gambling theory, employing computational techniques to analyze strategies and outcomes.

Findings

Discrete models differ significantly from continuous ones.

Computational methods provide new insights into gambling strategies.

Results highlight limitations of traditional continuous assumptions.

Abstract

The beautiful theory of statistical gambling, started by Dubins and Savage (for subfair games) and continued by Kelly and Breiman (for superfair games) has mostly been studied under the unrealistic assumption that we live in a continuous world, that money is indefinitely divisible, and that our life is indefinitely long. Here we study these fascinating problems from a purely discrete, finitistic, and computational, viewpoint, using Both Symbol-Crunching and Number-Crunching (and simulation just for checking purposes).