Crypto Pairs Trading: Cointegration, Stationarity, and Spread Reversion

Summary

This introduction to crypto pairs trading argues that correlation alone does not establish a durable relationship between two assets. A pair may move together because of shared market forces, yet its price spread can continue drifting. Cointegration offers a stronger basis for a relative value trade: although individual price series may be non-stationary, a hedged combination can form a stationary spread that tends to return toward an equilibrium.

The article uses synthetic examples to contrast a drifting spread with one that fluctuates around a stable mean. It outlines possible tools for implementation, including log prices, regression-based hedge ratios, spread z-scores, entry and exit thresholds, and tests of stationarity. It also recommends accounting for transaction costs, stops, and profit targets, and backtesting before using actual crypto pairs. These are conceptual foundations rather than demonstrated live results; stable relationships can change, and the article points to further testing as necessary.

Key ideas

• High correlation does not prove that a pair has a stable long-term relationship.
• Cointegration means a weighted combination of otherwise non-stationary prices can produce a stationary spread.
• A mean-reverting spread can provide a basis for entering and exiting relative value positions.
• Log prices, hedge ratios, and spread z-scores are tools for constructing and monitoring a pairs trade.
• Transaction costs, risk controls, backtesting, and ongoing checks are needed before practical use.

Tags

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