Pairs trade

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.^[1] The pair trading was pioneered by Gerry Bamberger and later led by Nunzio Tartaglia’s quantitative group at Morgan Stanley in the 1980s.^[2][3]

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 underperforming one, betting that the "spread" between the two would eventually converge.^[4] 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.

A notable pairs trader was hedge fund Long-Term Capital Management.^[5]

Contents

• 1 Examples of potentially correlated pairs
• 2 Model-based pairs trading
• 3 Market neutrality
• 4 Algorithmic pairs trading
• 5 Drift and risk management
• 6 References
• 7 External links

[edit] Examples of potentially correlated pairs

• Dow Jones (^DJI) and S&P500 (^GSPC)
• Coca-Cola (KO) and Pepsi (PEP)
• Wal-Mart (WMT) and Target Corporation (TGT)
• Dell (DELL) and Hewlett-Packard (HPQ)
• Exxon Mobil (XOM) and Chevron Corporation (CVX)
• Alliance and Leicester (AL.L) and Royal Bank of Scotland (RBS.L)
• Portugal Telecom (PTC.LS) and Telefonica (TEF.MC)
• Banco Comercial Português (MBC.LS) and Banco Português de Investimento (BPI.LS)

[edit] Model-based pairs trading

While it is commonly agreed that individual stock prices are difficult to forecast, there is evidence suggesting that it may be possible to forecast the price - the spread series - of certain stock portfolios. A common way to attempt this is by constructing the portfolio such that the spread series is a stationary process. To achieve spread stationarity in the context of pairs trading, where the portfolios only consist of two stocks, one can attempt to find a cointegration relationship between the two stock price series.^[6] This would then allow for combining them into a portfolio with a stationary spread series.^[7] Regardless of how the portfolio is constructed, if the spread series is a stationary processes, then it can be modeled, and subsequently forecasted, using techniques of time series analysis. Among those suitable for pairs trading are Ornstein-Uhlenbeck models,^[8] autoregressive moving average (ARMA) models^[9] and (vector) error correction models.^[10] Forecastability of the portfolio spread series is useful for traders because:

1. The spread can be directly traded by buying and selling the stocks in the portfolio, and
2. The forecast and its error bounds (given by the model) yield an estimate of the return and risk associated with the trade.

According to a paper of B. Do, R. Faff and K. Hamza, the success of pairs trading depends heavily on the modeling and forecasting of the spread time series.^[11]

[edit] Market neutrality

• 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^[12], since the short sale proceeds may be used to create the long position.

[edit] Algorithmic pairs trading

Today, pairs trading is often 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, automatically buying and selling to capitalize on market inefficiencies. The advantage in terms of reaction time allows traders to take advantage of tighter spreads.

[edit] Drift and risk management

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. A common way to model, and forecast, the spread for risk management purposes is by using autoregressive moving average models.

[edit] References

1. ^ The Application of Pairs Trading to Energy Futures Markets
2. ^ Bookstaber, Richard. A Demon Of Our Own Design, p. 186. Wiley, 2006.
3. ^ Lecture 23: Pairs Trading
4. ^ Lecture 23: Pairs Trading
5. ^ Lowenstein, Roger (2000). When Genius Failed: The Rise and Fall of Long-Term Capital Management. Random House. ISBN 0-375-50317-X 
6. ^ C. Alexander: "Market Models: A Guide to Financial Data Analysis". Wiley, 2001.
7. ^ A. D. Schmidt: "Pairs Trading - A Cointegration Approach". University of Sydney, 2008. http://ses.library.usyd.edu.au/bitstream/2123/4072/1/Thesis_Schmidt.pdf
8. ^ S. Mudchanatongsuk, J. A. Primbs and W. Wong: "Optimal Pairs Trading: A Stochastic Control Approach". Proceedings of the American Control Conference, 2008. http://www.nt.ntnu.no/users/skoge/prost/proceedings/acc08/data/papers/0479.pdf
9. ^ G. Vidyamurthy: "Pairs trading: quantitative methods and analysis". Wiley, 2004.
10. ^ A. D. Schmidt: "Pairs Trading - A Cointegration Approach". University of Sydney, 2008. http://ses.library.usyd.edu.au/bitstream/2123/4072/1/Thesis_Schmidt.pdf
11. ^ "A New Approach to Modeling and Estimation for Pairs Trading". Monash University, Working Paper. http://www.finanzaonline.com/forum/attachments/econometria-e-modelli-di-trading-operativo/1048428d1238757908-spread-e-pair-trading-pairstrading_binhdo.pdf
12. ^ http://www.thehedgefundguide.com/pairstrading.html

[edit] External links

• Pairs Trading, Convergence Trading, Cointegration by Daniel Herlemont
• Pairs-Trading in the Asian ADR Market
• Pairs Trading in the Russian Market