Cointegration is the statistical relationship between two or more time series, indicating that they move together over time despite short-term divergences. In other words, cointegration measures the long-term relationship between two or more variables.
Cointegration is particularly relevant to pairs trading strategies, which aim to profit from the divergence of two closely related assets. In pairs trading, two assets that have a long-term relationship are identified and traded based on the expectation that a short-term deviation from their long-term relationship will eventually revert to the mean.
To identify potential pairs for trading, pairs traders often use statistical measures such as the correlation coefficient between the two assets, but correlation only measures how two series move together in the short term, not the long term. Cointegration, on the other hand, provides a more reliable measure of the long-term relationship between two assets because it accounts for the fact that their prices may not move in perfect lockstep.
Once a cointegrated pair has been identified, pairs traders typically take a mean-reverting approach to trading. The basic idea of mean reversion is that if the prices of two assets have diverged significantly from their long-term mean, they are likely to revert to that mean eventually, providing an opportunity to profit from the expected convergence.
For example, suppose a pairs trader identifies a cointegrated pair of stocks, A and B, and observes that the ratio of their prices is currently significantly above its long-term mean. The trader might buy stock A and short sell an equivalent value of stock B, betting that the ratio will eventually revert to its mean and that the profits from the short sale will more than offset any losses on the long position. If the trader’s analysis was correct, they will make a profit as the prices eventually converge.
In summary, cointegration is a powerful tool for identifying pairs for trading and assessing the long-term relationship between two assets. Pairs traders can leverage this relationship to develop mean-reverting strategies that aim to profit from short-term divergences between the two assets.