Adaptive strategies in Kelly’s horse races model

We formulate an adaptive version of Kelly’s horse model in which the gambler learns from past race results using Bayesian inference. We characterize the cost of this gambling strategy and we analyze the asymptotic scaling of the difference between the growth rate of the gambler and the optimal growth rate, known as the gambler’s regret. We also explain how this adaptive strategy relates to the universal portfolio strategy, and we build improved adaptive strategies in which the gambler exploits the information contained in the bookmaker odds distribution.

JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

Volume: 2022
Issue: 9
Article Number: 093405

Published: SEP 2022

By: Despons, Armand ; Peliti, Luca ; Lacoste, David

DOI10.1088/1742-5468/ac8e58


Top



See also...

DNA nanotechnology to detect cancer biomarkers

How to detect diseases at the earliest stages of development? This is the problematic raised by most scientists and physicians, focusing on new (…) 

> More...

Frugal random exploration strategy for shape recognition using statistical geometry

Very distinct strategies can be deployed to recognize and characterize an unknown environment or a shape. A recent and promising approach, (…) 

> More...