Traders looking to expand their repertoire of available trading strategies, or enhance their existing skill set, might want to consider a deeper dive into pairs trading.

Pairs trading involves taking opposite but equal positions in two different underlying securities and are sometimes referred to as “intermarket spreads.” A key to the pairs approach is that it relies on a known, strong correlation (positive or negative) that exists between the two underlyings being considered for a spread. 

For example, imagine that the historical price movements of Exxon Mobil (XOM) and Chevron (CVX) exhibit a high degree of positive correlation (they do, in fact). If a price divergence presented itself, such that the correlation temporarily broke down, traders utilizing a pairs approach might view this as an opportunity to deploy a spread.

Pairs are most commonly used when trading equities and futures. For the latter group, some of the best-known pairs include oil vs. natural gas, gold vs. silver, wheat vs. corn, and many others. 

The foundation of pairs trades, as observed in these three examples, is that a strong positive or negative correlation has been established between the two over a long period of time. The ability to profit on a pairs position hinges on a belief that the pair will revert back to their historical average, after a temporary breakdown in correlation. 

In this regard, a trader deploying a pairs trade is banking on a widening or narrowing of the spread between the underlying prices of the two securities. At its core, a pairs trade therefore represents the expression of an opinion on the direction of the spread.

For example, gold and silver share a well-known positive correlation that hovers historically right around 0.89. The gold-silver pair is so famous that it even has its own ratio named after it: the gold-silver ratio.

This ratio is computed by simply taking the price per ounce of gold and dividing it by the price per ounce of silver, the result of which reports how many ounces of silver are required to purchase an ounce of gold. Because the gold-silver ratio can be tracked over time, traders can identify extremes in the ratio and attempt to profit off of “reversions” to the mean.

For reference, the gold-silver ratio has traded between roughly 40 and 90 over the last four decades, and the mean of the ratio is right around 65. When the ratio is at the lower end of that range, pairs traders consider buying gold, and selling silver, in hopes that the ratio will rise. Alternatively, pairs traders sell gold and buy silver when playing a potential decline in the ratio. 

From this example, one can see that identifying and deploying an attractive pairs trade depends on finding suitable pairs and tracking when correlations break down.

Traders seeking to take a deeper dive on pairs are recommended to review a new episode of Market Measures on the tastytrade financial network when scheduling allows. This particular episode explores new research conducted by tastytrade that highlights the importance of cointegration when it comes to identifying optimal pairs.

As outlined on the show, correlation is a great metric for reporting the degree to which a certain pair moves together, but cointegration appears to be an even more robust method of analyzing potential pairs trades because this metric better describes the mean reverting behavior of a given pair. 

Essentially, a cointegration analysis can provide traders with added confidence that a temporary breakdown in correlation will indeed revert to “normal” trading behavior. 

Because of the strong correlation/cointegration that exists between optimal pairs, there’s theoretically less risk in these trade structures when compared to deploying naked directional risk in a single underlying.

For added insight on these positions, traders may also want to review a previous installment of Best Practices which provides a step-by-step breakdown of the pairs trading methodology.

Sage Anderson is a pseudonym. The contributor has an extensive background in trading equity derivatives and managing volatility-based portfolios as a former prop trading firm employee. The contributor is not an employee of Luckbox, tastytrade or any affiliated companies. Readers can direct questions about topics covered in this blog post, or any other trading-related subject, to