论文标题
凯利的赛马模型中的自适应策略
Adaptive strategy in Kelly's horse races model
论文作者
论文摘要
我们制定了凯利（Kelly）马模型的自适应版本，其中赌徒使用贝叶斯推断从过去的比赛结果中学习。恢复了赌徒的生长速率和最佳生长速率（称为赌徒的sregret）之间的差异缩放。我们展示了这种自适应策略与通用投资组合策略的关系，并建立了改进的适应性策略，在这种策略中，赌徒利用簿记员分配中包含的信息以减少在学习阶段的最初资本损失。
We formulate an adaptive version of Kelly's horse model in which the gambler learns from past race results using Bayesian inference. A known asymptotic scaling for the difference between the growth rate of the gambler and the optimal growth rate, known as the gambler'sregret, is recovered. We show how this adaptive strategy is related to the universal portfolio strategy, and we build improved adaptive strategies in which the gambler exploits information contained in the bookmaker odds distribution to reduce his/her initial loss of the capital during the learning phase.
