英文标题：
《Stochastic Portfolio Theory: A Machine Learning Perspective》
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作者：
Yves-Laurent Kom Samo, Alexander Vervuurt
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最新提交年份：
2016
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英文摘要：
  In this paper we propose a novel application of Gaussian processes (GPs) to financial asset allocation. Our approach is deeply rooted in Stochastic Portfolio Theory (SPT), a stochastic analysis framework introduced by Robert Fernholz that aims at flexibly analysing the performance of certain investment strategies in stock markets relative to benchmark indices. In particular, SPT has exhibited some investment strategies based on company sizes that, under realistic assumptions, outperform benchmark indices with probability 1 over certain time horizons. Galvanised by this result, we consider the inverse problem that consists of learning (from historical data) an optimal investment strategy based on any given set of trading characteristics, and using a user-specified optimality criterion that may go beyond outperforming a benchmark index. Although this inverse problem is of the utmost interest to investment management practitioners, it can hardly be tackled using the SPT framework. We show that our machine learning approach learns investment strategies that considerably outperform existing SPT strategies in the US stock market.
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中文摘要：
在本文中，我们提出了一种新的应用高斯过程（GPs）的金融资产配置。我们的方法深深植根于随机投资组合理论（SPT），这是Robert Fernholz引入的一种随机分析框架，旨在灵活分析股票市场中某些投资策略相对于基准指数的表现。特别是，SPT展示了一些基于公司规模的投资策略，在现实假设下，这些策略在特定时间范围内以概率1跑赢基准指数。在这个结果的激励下，我们考虑了一个反问题，该问题包括（从历史数据中）学习基于任何给定交易特征集的最优投资策略，并使用用户指定的最佳性标准，该标准可能超越了超越基准指数的表现。尽管这个反问题对投资管理从业者来说是最重要的，但它很难用SPT框架来解决。我们表明，我们的机器学习方法学习的投资策略大大优于美国股市中现有的SPT策略。
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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：Quantitative Finance        数量金融学
二级分类：Mathematical Finance        数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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一级分类：Statistics        统计学
二级分类：Machine Learning        机器学习
分类描述：Covers machine learning papers (supervised, unsupervised, semi-supervised learning, graphical models, reinforcement learning, bandits, high dimensional inference, etc.) with a statistical or theoretical grounding
覆盖机器学习论文（监督，无监督，半监督学习，图形模型，强化学习，强盗，高维推理等）与统计或理论基础
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