Stationarity Quant Interview Guide
Stationarity quant interview guide covering stationary series, unit roots, rolling behavior, regimes, examples, and caveats.
Candidates discussing time-series stability and mean-reversion assumptions.
Stationarity means stable distributional behavior
A stationary series has statistical properties that do not drift arbitrarily over time, depending on the definition being used.
Mean reversion often needs stationarity
Many spread and pairs strategies assume a residual or spread has a stable mean and variance over the relevant horizon of trading.
Concrete example
A price series may trend and be non-stationary, while a properly hedged spread between related assets may look more stable.
Tests have limits
Unit-root and stationarity tests can be sensitive to sample length, structural breaks, lag choices, and changing regimes.
Common mistakes
Candidates often say a failed test kills a strategy or a passed test proves it. Both conclusions are too strong for markets.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.