A stress test asks how a strategy behaves when conditions are unkind rather than average. It replays the rules across difficult historical windows — crashes, choppy ranges, violent rallies — and can layer on adversarial shocks such as extra slippage, rejected fills, or shuffled price series.
The point is not the headline return but survival: a strategy that only works in calm trends but bleeds in chop or gaps is fragile. Stress testing surfaces that fragility before live capital does.
Exemple
A trend strategy that returns 30% in backtest loses 18% when the stress test injects 2× slippage and replays the March 2020 crash window.
Comment Noon Barbari utilise Stress Test
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Stress-test a strategy in noonbarbari →Termes liés
- Risque
Maximum drawdown
The deepest peak-to-trough decline observed across the entire equity curve.
- Backtesting
Slippage
Difference between the price a strategy assumed and the price it actually got.
- Backtesting
Monte Carlo Simulation
Resampling trade outcomes many times to get a distribution of results instead of one number.
- Backtesting
Walk-forward optimization
Optimize on a rolling in-sample window, validate on the next out-of-sample slice.