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Pairs Trading: Performance of a Relative Value Arbitrage Rule

Author

Listed:
  • William Goetzmann

    (Yale School of Management)

  • Evan g. Gatev

    (Boston College - Department of Finance)

  • K. Geert Rouwenhorst

    (Yale School of Management)

Abstract

We test a Wall Street investment strategy known as "pairs trading" with daily data over the period 1962 through 1997. Stocks are matched into pairs according to minimum distance in historical normalized price space. We test the profitability of several trading rules with six-month trading periods over the 1962-1997 period, and find average annualized excess returns of up to 12 percent for a number of self-financing portfolios of top pairs. Part of these profits may be due to market microstructure effects. Nevertheless, our historical trading profits exceed a conservative estimate of transaction costs through most of the period. We bootstrap random pairs in order to distinguish pairs trading from pure mean-reversion strategies. The bootstrap results suggest that the ?pairs? effect differs from previously documented mean reversion profits.

Suggested Citation

  • William Goetzmann & Evan g. Gatev & K. Geert Rouwenhorst, 1998. "Pairs Trading: Performance of a Relative Value Arbitrage Rule," Yale School of Management Working Papers ysm3, Yale School of Management.
  • Handle: RePEc:ysm:somwrk:ysm3
    as

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    References listed on IDEAS

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    1. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    2. Mark J Ready, 2002. "Profits from Technical Trading Rules," Financial Management, Financial Management Association, vol. 31(3), Fall.
    3. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    4. Chen, Zhiwu & Knez, Peter J, 1995. "Measurement of Market Integration and Arbitrage," Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 287-325.
    5. Bossaerts, Peter, 1988. "Common nonstationary components of asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 347-364.
    6. KENT D. DANIEL & David Hirshleifer & AVANIDHAR SUBRAHMANYAM, 2004. "A Theory of Overconfidence, Self-Attribution, and Security Market Under- and Over-reactions," Finance 0412006, University Library of Munich, Germany.
    7. Petersen, Mitchell A. & Fialkowski, David, 1994. "Posted versus effective spreads *1: Good prices or bad quotes?," Journal of Financial Economics, Elsevier, vol. 35(3), pages 269-292, June.
    8. Charles M. C. Lee & James Myers & Bhaskaran Swaminathan, 1999. "What is the Intrinsic Value of the Dow?," Journal of Finance, American Finance Association, vol. 54(5), pages 1693-1741, October.
    9. Jegadeesh, Narasimhan & Titman, Sheridan, 1995. "Overreaction, Delayed Reaction, and Contrarian Profits," Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 973-993.
    10. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    11. repec:hrv:faseco:30721347 is not listed on IDEAS
    12. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    13. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

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