Pairs trading, developed by analysts at Morgan Stanley in the 1980s, uses correlation between two similar investment vehicles to create a market-neutral trading strategy – where profits are not related to whether the overall market goes up or down.
Correlation of two investment vehicles refers to how their prices change relative to each other. If their movements correlated perfectly, they would have a correlation factor of 1. If the prices moved in exactly opposite directions, they have a correlation of -1. Random, unrelated movements have a correlation of zero.
Often, stocks that are in the same sector react similarly to market conditions because factors that affect one affect the other as well. To engage in pairs trading, you look for investment pairs within a sector that have historically high correlation, usually over 0.8-0.9, and monitor them for uncharacteristic changes in that correlation.
If there is reason to believe the change is transient and conditions will return to normal, you sell (take a short position in) the stock that is relatively outperforming, and buy (take a long position in) an equal dollar amount in the stock that is underperforming. You adjust your holdings as the correlation returns to normal.
In essence, you are not betting that either stock will go up or down, you are betting that the gap between them will close based on predictive historical data. As long as the gap closes and you time the exit properly, you made money whether the overall market went up or down.
This method also applies to commodity pairs, options, futures, or currencies. It is possible to do this across platforms (such as correlating oil with oil stocks), but many pairs traders stay within a particular sector.
There are still risks with this strategy, manifesting themselves in three typical failure modes:
- Invalid Model – The most obvious one is that the gap does not close, but keeps on widening or reaches a new long-term equilibrium because of a disruptive, more permanent change in conditions that invalidates the model..
- Execution Flaws – One of your orders was not fully filled or filled at a slightly different price than expected, reducing your profit margin.
- Bad Exit Strategy – Your exit should be based on a particular expectation of profit. In case the gap is not closing and things are going poorly, you need a stop-loss order or some other trigger in order to minimize your losses.
Thanks to the Internet, you can easily access plenty of information on past pricing information, correlation factors, spreads, and other data relevant to pairs trading. Online trading sites have the tools to help you make your own charts for analysis, or you can download data and manipulate it yourself in Excel if you are so inclined.
Once you have found correlated pairs to monitor, you need to decide how much of a gap, or spread, is sufficient for you to act. This is typically based on a given number of standard deviations away from the normal spread. Again, online tools can help with this analysis.
Next, decide how you are going to verify your analysis. Can you find a reason for the spread that affects one company but not the other? Has one company outflanked the other in a way that is likely to be permanent and not temporary? How will you balance technical analysis and trends, fundamental analysis based on the company’s financial metrics, and public information about the company’s products, prospects and liabilities?
Finally, you will need to set up your exit strategy based on your expectations of profit and tolerance for risk. Also take into account the fees and commissions (since each move involves two market actions, the fees are double that of a simple transaction), and the relative volatility of the stock (how quickly do gaps close historically) as you set your boundaries.
If you find the concept appealing, do some initial research and perform some “mock” trades to see how you fare before entering the real market. Just remember that there are significant risks involved, and plenty of people trying to do the same thing you are – so don’t skimp on your research.