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用于可解释期货配对交易的路径签名指标

文章 arXiv papers · 作者: Zihao Guo et al.
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总结

本文提出一种期货配对交易策略，使用路径签名作为时间序列特征。研究将签名分解为两个指标：衡量路径交互性的分段签名指标，以及衡量方向的增量协变指标。这两个指标在策略设计中充当过滤器，旨在生成比一些基于统计套利或深度学习的方法更容易解释且更稳定的信号。

据报告，在分钟级期货数据上的实验显示，相比传统配对交易方法，该策略收益更高、最大回撤更低，夏普比率也更高。这些发现属于实证结果，取决于所测试的数据和实现方式。所提供的描述未说明具体合约、样本时期、成本、对比策略细节或稳健性检验，因此不足以评估其现实盈利能力或跨市场泛化能力。

核心观点

  • 使用路径签名表示期货价格路径，以生成配对交易信号。
  • 该方法将路径信息分解为交互性指标和方向性协变指标。
  • 所提出的策略将这两个指标用作过滤器。
  • 分钟级期货实验报告称，相比传统配对交易，收益更高、最大回撤更低，夏普比率也更高。
  • 所提供的描述缺少足够细节，无法评估交易成本或测试数据之外的泛化能力。

标签

期货配对交易高频交易统计学风险管理
全文
# Signature Decomposition Method Applying to Pair Trading


# Signature Decomposition Method Applying to Pair Trading









High-frequency quantitative trading strategies have long been of significant interest in futures market. While advanced statistical arbitrage and deep learning enhance high-frequency data processing, they diminish opportunities for traditional methods and yield less interpretable, unstable strategies. Consequently, developing stable, interpretable quantitative strategies remains a priority in futures markets. In this study, we propose a novel pair trading strategy by leveraging the mathematical concept of path signature which serves as a feature representation of time series. Specifically, the path signature is decomposed into two new indicators: the path interactivity indicator segmented signature and the directional indicator covariation of increments, which serve as double filters in strategy design. Empirical experiments using minute-level futures data show our strategy significantly outperforms traditional pair trading, delivering higher returns, lower maximum drawdown, and higher Sharpe ratio. The proposed method enhances interpretability and robustness while maintaining strong returns, demonstrating the potential of path signatures in financial trading.

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。