Pairs Trading (Statistical Arbitrage)
Also known as: statistical arbitrage, relative-value arbitrage, mean-reversion pairs strategy, Çift Alım-Satım Stratejisi (Pairs Trading / Statistical Arbitrage)
Pairs trading is a quantitative trading strategy that takes a long-short position on two cointegrated assets when the gap (spread) between their prices shows mean reversion. It was popularised as a relative-value arbitrage rule by Gatev, Goetzmann and Rouwenhorst (2006) and framed quantitatively by Vidyamurthy (2004).
Key highlights
- Market-neutral: profit depends on the relative move of the two assets, not on the overall market direction.
- Grounded in a testable statistical relationship — cointegration and mean reversion can be checked before trading.
- The Ornstein-Uhlenbeck framing gives an explicit half-life that signals how quickly trades should resolve.
Intuition
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How it works
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When to use it
Use pairs trading on two continuous price series that are economically related and statistically cointegrated, with a long enough history (at least about 250 observations) to estimate the relationship reliably. It is appropriate when the spread is stationary and mean-reverting (ADF p < 0.05), the half-life of reversion is short enough to act on (typically under 30 days), and trading costs and slippage are accounted for. It is unsuitable when the cointegration relationship breaks down (a regime change), so that risk must be monitored continuously.
Strengths & limitations
- Market-neutral: profit depends on the relative move of the two assets, not on the overall market direction.
- Grounded in a testable statistical relationship — cointegration and mean reversion can be checked before trading.
- The Ornstein-Uhlenbeck framing gives an explicit half-life that signals how quickly trades should resolve.
- Requires a genuine cointegration relationship; spurious or unstable pairs lead to losses.
- The cointegration can break (regime change), and a spread that stops reverting can produce large drawdowns.
- Returns are sensitive to transaction costs and slippage, which can erode the small per-trade edge.
Common pitfalls
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Applications
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Frequently asked
How do I find a tradeable pair?
Look for two economically related assets and test them for cointegration with the Engle-Granger or Johansen test. If the pair is cointegrated, form the spread using the hedge ratio and confirm it is stationary with an ADF test (p < 0.05).
What is the half-life and why does it matter?
The half-life t₁/₂ = ln 2 / θ comes from the Ornstein-Uhlenbeck model and measures how long the spread takes to close half of a deviation from its mean. A short half-life (typically under 30 days) means trades resolve quickly; a long one means the spread may not revert within a useful horizon.
Is pairs trading really market-neutral?
Because you are long one asset and short the other, the strategy's profit depends on the relative move of the pair rather than the market's overall direction. It is approximately market-neutral as long as the cointegration relationship holds.
What is the biggest risk?
A regime change that breaks the cointegration relationship: the spread stops reverting and keeps widening, producing large losses. This is why the relationship must be monitored continuously, alongside transaction costs and slippage.
Sources
- 1.Gatev, E., Goetzmann, W. N. & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. Review of Financial Studies, 19(3), 797–827.
- 2.Vidyamurthy, G. (2004). Pairs Trading: Quantitative Methods and Analysis. Wiley.ISBN 978-0471460671
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Cite this page
ScholarGate. (2026, June 1). Pairs Trading. ScholarGate. https://scholargate.app/finance/pairs-trading