Signature Decomposition Method Applying to Pair Trading

TL;DR

This paper introduces a novel pair trading strategy using path signatures to create interpretable and robust indicators, significantly improving performance over traditional methods in futures markets.

Contribution

It develops a new pair trading approach based on path signature decomposition, enhancing interpretability and robustness with empirical validation.

Findings

Strategy outperforms traditional pair trading with higher returns

Achieves lower maximum drawdown

Provides higher Sharpe ratio

Abstract

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.