Pairs Trading Strategy: Cointegration Test
In the world of quantitative trading, pairs trading has emerged as a powerful market-neutral strategy that capitalizes on the relative price movements b...
In the world of quantitative trading, pairs trading has emerged as a powerful market-neutral strategy that capitalizes on the relative price movements between two historically correlated assets. This approach, which dates back to the 1980s when Morgan Stanley pioneered the technique, relies on statistical relationships rather than directional market bets. At its core, successful pairs trading depends on identifying cointegrated asset pairs—those that maintain a long-term equilibrium relationship despite short-term deviations. This article explores the statistical foundation of cointegration, practical implementation techniques, and how to build a robust pairs trading strategy that can profit from market volatility while minimizing exposure to broad market movements. Cointegration is a statistical property that describes a long-term equilibrium relationship between two or more non-stationary time series. It's the key concept that separates robust pairs trading from mere correlation-based trading. Stationarity is a statistical property where a time series has constant mean and variance over time, making it predictable.