The optimal betting wealth growth rate
Ashwin Ram, Aaditya Ramdas

TL;DR
This paper determines the maximum possible wealth growth rate in a Kelly betting game against an arbitrary alternative distribution, generalizing previous results and providing conditions for optimal sequential testing.
Contribution
It introduces a new characterization of the optimal growth rate using KL divergence and extends recent results to the sequential setting.
Findings
The optimal growth rate equals a limit involving KL divergence and bipolar sets.
When the infimum KL divergence is weakly lower semicontinuous, the two key quantities are equal.
Provides necessary and sufficient conditions for the existence of power-one sequential tests.
Abstract
This paper characterizes the best possible rate of growth of wealth in a Kelly betting game when repeatedly betting against a general i.i.d. null hypothesis , but the data are drawn i.i.d from an arbitrary alternative . We prove that it equals , where and is its bipolar, i.e., this rate is achievable and one cannot do better. This quantity is in general smaller than a more popular quantity in the literature, . If is weakly lowersemicontinuous (w.l.s.c.) at , we show that the two quantities are equal; in particular, this happens when is weakly compact. For simple…
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