The pairs trade or pair trading is a market neutral trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy.The pair trading was pioneered by Nunzio Tartaglia’s quantitative group at Morgan Stanley in the 1980's. When the correlation between the two securities temporarily weakens, i.e. one stock moves up while the other moves down, the pairs trade would be to short the outperforming stock and to long the under performing one, betting that the “spread” between the two would eventually converge.The divergence within a pair can be caused by temporary supply/demand changes, large buy/sell orders for one security, reaction for important news about one of the companies, and so on.Pairs trading strategy demands good position sizing, market timing, and decision making skill. Although the strategy does not have much downside risk, there is a scarcity of opportunities, and, for profiting, the trader must be one of the first to capitalize on the opportunity.The pairs trade helps to hedge sector- and market-risk. For example, if the whole market crashes, and the two stocks plummet along with it, the trade should result in a gain on the short position and a negating loss on the long position, leaving the profit close to zero in spite of the large move.

Pairs trade is a mean-reverting strategy, betting that the prices will eventually revert to their historical trends.
Pairs trade is a self-funding strategy, since the short sale proceeds may be used to create the long position.

Trading pairs is not a risk-free strategy. The difficulty comes when prices of the two securities begin to drift apart, i.e. the spread begins to trend instead of reverting back to the original mean. Dealing with such adverse situations requires strict risk management rules, which have the trader exit an unprofitable trade as soon as the original setup—a bet for reversion to the mean—has been invalidated. This can be achieved, for example, by forecasting the spread and exiting at forecast error bounds.