Path Signature Indicators for Interpretable Futures Pair Trading

Summary

The paper proposes a futures pair-trading strategy that uses path signatures as time-series features. It decomposes the signature into two indicators: a segmented signature measure of path interactivity and a covariation-of-increments measure of direction. These indicators act as two filters in the strategy design, with the goal of producing signals that are more interpretable and stable than some approaches based on statistical arbitrage or deep learning.

Experiments on minute-level futures data reportedly show higher returns, lower maximum drawdown, and a higher Sharpe ratio than traditional pair-trading methods. The findings are empirical and depend on the data and implementation tested. The provided description does not specify the instruments, sample period, costs, comparison strategy details, or robustness checks, so it is not enough to assess real-world profitability or generalization across markets.

Key ideas

• Path signatures are used to represent futures price paths for pair-trading signals.
• The method decomposes path information into an interactivity indicator and a directional covariation indicator.
• The two indicators are used as filters in the proposed strategy.
• Minute-level futures experiments report stronger returns, lower maximum drawdown, and a higher Sharpe ratio than traditional pair trading.
• The supplied description does not give enough detail to assess transaction costs or generalization beyond the tested data.

Tags

# 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.

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