摘要翻译：
本文推导了一个鲁棒的在线股票交易算法，该算法实现了事后最优配对再平衡规则的最终财富的最大可能百分比。成对再平衡规则选择市场上的某一对股票，然后永久地执行再平衡交易，以保持这两个股票中每一个的目标财富份额。在每一次离散的市场波动后，配对再平衡规则将出售精确数量的表现优异的股票，并将收益投入表现不佳的股票。在典型的情况下，事后来看，人们可以找到两个重新平衡的规则，这些规则将惊人地击败市场。我们的交易策略扩展了Ordentlich and Cover(1998)的“最大最小万能投资组合”，保证实现事后最优财富的可接受百分比，该百分比在缓慢的（多项式）速度下趋于零。这意味着，在足够长的投资范围内，交易者可以执行一个复合年增长率，该增长率可以任意接近事后最佳配对再平衡规则。如果事实证明存在一个配对再平衡规则，即资本增长的渐近速度高于市场指数，那么该策略将“渐近地击败市场”。与Ordentlich和Cover(1998)策略相比，我们的算法有两个优点。首先，他们的策略在实践中是不可能计算的。第二，在考虑更适度的基准（而不是事后看来最好的全股票再平衡规则）时，我们降低了“普遍性成本”，实现了更高的学习率。
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英文标题：
《Super-Replication of the Best Pairs Trade in Hindsight》
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作者：
Alex Garivaltis
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最新提交年份：
2019
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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：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Economics        经济学
二级分类：Theoretical Economics        理论经济学
分类描述：Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Quantitative Finance        数量金融学
二级分类：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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英文摘要：
  This paper derives a robust on-line equity trading algorithm that achieves the greatest possible percentage of the final wealth of the best pairs rebalancing rule in hindsight. A pairs rebalancing rule chooses some pair of stocks in the market and then perpetually executes rebalancing trades so as to maintain a target fraction of wealth in each of the two. After each discrete market fluctuation, a pairs rebalancing rule will sell a precise amount of the outperforming stock and put the proceeds into the underperforming stock. Under typical conditions, in hindsight one can find pairs rebalancing rules that would have spectacularly beaten the market. Our trading strategy, which extends Ordentlich and Cover's (1998) "max-min universal portfolio," guarantees to achieve an acceptable percentage of the hindsight-optimized wealth, a percentage which tends to zero at a slow (polynomial) rate. This means that on a long enough investment horizon, the trader can enforce a compound-annual growth rate that is arbitrarily close to that of the best pairs rebalancing rule in hindsight. The strategy will "beat the market asymptotically" if there turns out to exist a pairs rebalancing rule that grows capital at a higher asymptotic rate than the market index. The advantages of our algorithm over the Ordentlich and Cover (1998) strategy are twofold. First, their strategy is impossible to compute in practice. Second, in considering the more modest benchmark (instead of the best all-stock rebalancing rule in hindsight), we reduce the "cost of universality" and achieve a higher learning rate.
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PDF链接：
https://arxiv.org/pdf/1810.02444