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Optimizing Entry and Exit Thresholds for Mean-Reverting Pairs Trades

Code Stratmill research code

Summary

This module implements analytic methods for selecting entry and exit thresholds for a mean-reverting spread, following a published optimal-threshold framework. It transforms thresholds into dimensionless units using the model’s mean-reversion speed, long-run level, and volatility, solves the paper’s threshold equations numerically, and converts the solutions back into spread units. It exposes both a conventional rule and a newer rule, which return threshold sets for long and short positions.

The class also computes expected trade duration and its variance, then uses these quantities with transaction costs to estimate expected return, return variance, and a Sharpe ratio that accounts for a risk-free rate. Plotting helpers examine how outputs vary with costs or rates. These are model-based calculations rather than empirical performance evidence: the excerpt provides no dataset, backtest, or trading results. Estimates depend on the mean-reverting model and its parameter inputs, and the numerical root solver’s output can depend on its initial guess.

Key ideas

  • The method derives threshold rules for trading a mean-reverting series and provides conventional and revised variants.
  • It rescales spread thresholds using mean-reversion, volatility, and long-run level parameters.
  • Expected trade duration and duration variance feed into return and Sharpe ratio calculations.
  • Transaction costs affect expected returns, while the risk-free rate is incorporated into the Sharpe calculation.
  • The provided material contains model implementation details but no empirical validation or performance results.

Tags

Pairs tradingMean reversionStatisticsRisk management

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.