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A mathematical study of the excess growth rate

Published: October 29, 2025 | arXiv ID: 2510.25740v1

By: Steven Campbell, Ting-Kam Leonard Wong

Potential Business Impact:

Helps money grow faster by understanding information.

Business Areas:
A/B Testing Data and Analytics

We study the excess growth rate -- a fundamental logarithmic functional arising in portfolio theory -- from the perspective of information theory. We show that the excess growth rate can be connected to the R\'{e}nyi and cross entropies, the Helmholtz free energy, L. Campbell's measure of average code length and large deviations. Our main results consist of three axiomatic characterization theorems of the excess growth rate, in terms of (i) the relative entropy, (ii) the gap in Jensen's inequality, and (iii) the logarithmic divergence that generalizes the Bregman divergence. Furthermore, we study maximization of the excess growth rate and compare it with the growth optimal portfolio. Our results not only provide theoretical justifications of the significance of the excess growth rate, but also establish new connections between information theory and quantitative finance.

Repos / Data Links

Page Count
54 pages

Category
Computer Science:
Information Theory