摘要翻译：
本文研究了在一个潜在过程的瞬时期望收益未知的市场中，如何以稳健增长最优的方式进行投资的问题。利用椭圆型二阶微分算子的广义主本征函数辨识最优投资策略，它依赖于用于投资的基本过程的协方差结构。在Fernholz和Karatzas的术语[Ann.appl.probab.20(2010)1179-1204]中，稳健增长最优策略也可以被看作是最优套利的一个极限，因为终端日期达到无穷大。
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英文标题：
《Robust maximization of asymptotic growth》
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作者：
Constantinos Kardaras, Scott Robertson
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最新提交年份：
2012
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Portfolio Management        项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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英文摘要：
  This paper addresses the question of how to invest in a robust growth-optimal way in a market where the instantaneous expected return of the underlying process is unknown. The optimal investment strategy is identified using a generalized version of the principal eigenfunction for an elliptic second-order differential operator, which depends on the covariance structure of the underlying process used for investing. The robust growth-optimal strategy can also be seen as a limit, as the terminal date goes to infinity, of optimal arbitrages in the terminology of Fernholz and Karatzas [Ann. Appl. Probab. 20 (2010) 1179-1204].
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PDF链接：
https://arxiv.org/pdf/1005.3454