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基于反馈控制的配对交易方法

文章 arXiv papers · 作者: Atul Deshpande et al.
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总结

本文提出一种以反馈控制问题为框架的通用配对交易算法。交易者可以选择一大类价差函数，并随价差变化动态调整投资水平。该方法不依赖对股票价格过程和价差形式的严格假设，而是在价差与价格过程共同满足均值回归条件时，将一对资产定义为可交易。在这些情况下，作者证明该算法能带来正的预期账户增长。

论文还报告了历史交易数据测试：将股票配对拟合到一种常用价差函数，并称模拟结果显示增长稳健且没有特别大的回撤。这些结果支持该方法在测试场景中的表现，但现有描述未给出具体业绩数据，也未说明成本、执行或样本外验证情况。理论增长结果以所述均值回归条件为前提，并不保证任意配对或实盘交易都能实现。

核心观点

  • 该算法将选定的价差函数作为反馈，动态调整投资水平。
  • 当价差与价格过程满足均值回归条件时，一对股票才符合可交易定义。
  • 作者证明在该条件下，账户预期增长为正。
  • 历史数据测试和模拟报告了稳健增长，且没有特别大的回撤。
  • 所述证据无法证明实盘表现，也未计入未说明的交易成本和执行细节。

标签

配对交易均值回归股票风险管理回测
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# A General Framework for Pairs Trading with a Control-Theoretic Point of View


# A General Framework for Pairs Trading with a Control-Theoretic Point of View









Pairs trading is a market-neutral strategy that exploits historical correlation between stocks to achieve statistical arbitrage. Existing pairs-trading algorithms in the literature require rather restrictive assumptions on the underlying stochastic stock-price processes and the so-called spread function. In contrast to existing literature, we consider an algorithm for pairs trading which requires less restrictive assumptions than heretofore considered. Since our point of view is control-theoretic in nature, the analysis and results are straightforward to follow by a non-expert in finance. To this end, we describe a general pairs-trading algorithm which allows the user to define a rather arbitrary spread function which is used in a feedback context to modify the investment levels dynamically over time. When this function, in combination with the price process, satisfies a certain mean-reversion condition, we deem the stocks to be a tradeable pair. For such a case, we prove that our control-inspired trading algorithm results in positive expected growth in account value. Finally, we describe tests of our algorithm on historical trading data by fitting stock price pairs to a popular spread function used in literature. Simulation results from these tests demonstrate robust growth while avoiding huge drawdowns.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。