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动态交易策略的路径游程分析

文章 arXiv papers · 作者: Anna Ananova et al.
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总结

本文介绍一种无需模型、逐路径分析动态策略风险与收益的方法，适用于配对交易、均值回归和统计套利等策略。该方法将连续交易信号分解为 δ-游程，即偏离参考水平后又回到该水平的变动。该方法不需要概率假设，并利用这种分解推导交易次数、已实现利润、最大亏损和回撤等情景指标。

本文还将均值回归策略的高频极限与信号的高阶局部时联系起来，为不规则路径中的局部时赋予金融解释。文中介绍一种非参数情景模拟方法，可生成游程特征与实证观察相符的路径。摘要未说明交易规则、校准流程或验证结果，因此介绍的是分析框架和模拟思路，而非完整详尽的实施方案。

核心观点

  • 连续信号路径可以唯一分解为偏离参考水平、幅度达到指定值的游程。
  • 游程计数可用于计算交易次数、已实现利润、最大亏损和回撤等情景指标。
  • 该框架无需概率假设，逐路径分析策略风险与收益。
  • 均值回归策略的高频行为与信号的局部时相关联。
  • 非参数模拟可以生成与观察到的游程特征相符的路径。

标签

配对交易均值回归统计学风险管理回测
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# Model-free Analysis of Dynamic Trading Strategies


# Model-free Analysis of Dynamic Trading Strategies









We introduce a model-free approach for analyzing the risk and return for a broad class of dynamic trading strategies, including pairs trading, mean-reversion trading and other statistical arbitrage strategies, in terms of excursions of a trading signal away from a reference level. Our results are derived in a pathwise setting, without any probabilistic assumptions. We introduce the notion of δ-excursion, defined as a path which deviates by δ from a reference level before returning to this level. We show that every continuous path has a unique decomposition into δ-excursions. This decomposition is useful for the scenario analysis of dynamic trading strategies, leading to simple expressions for the number of trades, realized profit, maximum loss, and drawdown. We show that the high-frequency limit of mean-reversion strategies may be described in terms of the (p-th order) local time of the signal. In particular, our results yield a financial interpretation of the local time of an irregular path. Finally, we describe a non-parametric scenario simulation method for generating paths whose excursion properties match those observed in empirical data.

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。