Markov Regime Switching for Pairs Trading

Summary

This method adapts mean-reversion pairs trading to the risk that a spread shift reflects a lasting structural change rather than a temporary deviation. It models the pair spread as having two Markov-switching states, each with its own mean and volatility, and estimates the current state and state probabilities using a rolling window.

Trades are triggered when the spread moves beyond a state-specific standard deviation threshold. The rules use a probability threshold for selected entries and exits, with actions also depending on whether the current position is long, short, or flat. The workflow selects a pair, constructs its spread, fits the regime model, generates signals, and maps signals to position changes. The documentation cites a published paper and provides an illustrative implementation example, but gives no performance results here. Outcomes depend on pair selection, spread construction, parameter estimates, and whether the regime model identifies structural breaks in time; the method does not eliminate those risks.

Key ideas

• The strategy distinguishes temporary spread deviations from persistent shifts by modeling two regimes.
• Each regime has a separate spread mean and volatility, estimated with a rolling window.
• State probabilities and standard deviation thresholds govern entries and exits.
• Pair selection and spread construction are separate design choices that affect the strategy.
• The provided material explains rules and implementation steps but reports no empirical performance evidence.

Tags

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