The pairs trade (pairs trading) was developed in the late 1980s by quantitative analysts. They found that certain securities, often competitors in the same sector, were correlated in their day-to-day price movements. When the correlation broke down, i.e. one stock traded up while the other traded down, they would sell the outperforming stock and buy the under performing one, betting that the “spread” between the two would eventually converge.
Some real-life examples of potentially correlated pairs:
- Coca-Cola (KO) and Pepsi (PEP)
- Wal-Mart (WMT) and Target (TGT)
- Dell (DELL) and Hewlett-Packard (HPQ)
- Ford (F) and General Motors (GM)
- BHP Billiton (BHP) and Rio Tinto (RIO)
The pairs trade helps to hedge sector- and market-risk. For example, if the market as a whole crashes and your two stocks plummet along with it, you should experience a gain on the short position and a negating loss on the long position, leaving your profit close to zero in spite of the large move. In a pairs trade, you are not making a bet on the direction of the stocks in absolute terms, but on the direction of the stocks relative to each other.
Algorithmic Pairs Trading
Today, Pairs trading is often conducted using algorithmic trading strategies on an Execution Management System in research papers. These strategies are typically built around models that define the spread based on historical data mining and analysis. The algorithm monitors for deviations in price, automatically buying and selling to capitalize on market inefficiencies. The advantage in terms of reaction time allows that traders to take advantage of tighter spreads.