Wall Street has long been interested in quantitative methods of speculation. One popular short-term speculation strategy is known as “pairs trading”. The strategy has at least a 30-year history on Wall Street and is among the proprietary "statistical arbitrage" tools currently used by hedge funds as well as investment banks. The concept of pairs trading is disarmingly simple. Find two stocks whose prices have moved together historically. When the spread between them widens, short the winner and buy the loser. If history repeats itself, prices will converge and the arbitrageur will profit.
It is hard to believe that such a simple strategy, based solely on past price dynamics and simple contrarian principles, could possibly make money. If the equity market were efficient at all times, risk-adjusted returns from pairs trading should not be positive! But real market condition shows, this strategy delivers consistent profits with minimum risk. In fact, pair trading makes the market efficient…
What is Stock Pair Trading?
The pair trading was pioneered by Alfred Winslow Jones in 1950s, but boom came with Gerry Bamberger and later Nunzio Tartaglia’s quantitative group at Morgan Stanley in the 1980s.
In the mid-1980s, the Wall Street quant Nunzio Tartaglia assembled a team of physicists, mathematicians, and computer scientists to uncover arbitrage opportunities in the equities markets. Tartaglia’s group of former academics used sophisticated statistical methods to develop high-tech trading programs, executable through automated trading systems, which took the intuition and trader’s “skill” out of arbitrage and replaced it with disciplined, consistent filter rules.
Among other things, Tartaglia’s programs identified pairs of securities whose prices tended to move together. They traded these pairs with great success in 1987—a year when the group reportedly made a $50 million profit for the firm. Although the Morgan Stanley group disbanded in 1989 after a couple of bad years of performance, pairs trading has since become an increasingly popular”market neutral” investment strategy used by individual and institutional traders as well as hedge funds.
The increased popularity of quantitative-based statistical arbitrage strategies has also apparently affected profits. In a New York Times interview, David Shaw, head of one of the most successful modern quant shops and himself an early Tartaglia’s protege, suggests that recent pickings for quant-shops have become slim—he attributes the success of his firm, D. E. Shaw, to early entry into the business. Tartaglia’s own explanation for pairs trading is psychological. He claims, ‘‘… Human beings don’t like to trade against human nature, which wants to buy stocks after they go up not down’’ [Hansell (1989)]. Could pairs traders be the disciplined investors taking advantage of the undisciplined over-reaction displayed by individual investors? This is at least one possible—albeit psychological—explanation for our results, which is consistent with Jegadeesh and Titman’s (1995) finding that contrarian profits are in part due to over-reaction to company-specific information shocks rather than price reactions to common factors.
Since that time pair trading is essential part of trading strategy of institutional traders as well as hedge funds. Pairs trading is conducted using algorithmic trading strategies on an Execution Management System. 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 and automatically suggest buying and selling orders to capitalize on market inefficiencies.