Cross-Commodity Futures Arbitrage Using Spread and Ratio Reversion

Summary

This article introduces cross-commodity futures arbitrage as trading the relative price of two related contracts, typically entering opposing positions when their spread or ratio moves away from an expected range and closing as it reverts. It groups candidate pairs into substitute products, such as related oils or meals, and products linked through an industrial chain, such as raw materials and processed goods. It recommends assessing relationships with cointegration tests, linear regression, and residual stationarity rather than relying only on simple correlation.

For a basic spread strategy, it proposes estimating a rolling mean and standard deviation from recent daily observations, then setting entry, exit, and stop thresholds. Its example uses a 30-day window, entries at three-quarters of a standard deviation from the mean, and stops at two standard deviations; positions are taken against extreme spreads and closed near the mean. The text stresses that these trades remain risky, that fundamental context matters, and that contract sizes should be matched by notional value when per-contract values differ. It provides no backtest or evidence that the example thresholds are robust.

Key ideas

• Cross-commodity trades seek to profit when related futures prices move back toward a historical spread or ratio.
• Candidate relationships can arise from product substitution or shared industrial-chain economics.
• Cointegration and stationary regression residuals are suggested for evaluating long-run relationships.
• The example strategy uses rolling spread statistics to define entries, mean exits, and stop losses.
• Position sizing should account for contract notional, and convergence trades can still incur substantial losses.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.