MAE

What it is

MAE stands for Maximum Adverse Excursion — the worst unrealized loss a trade reached at any point during the hold, regardless of how the trade ended. If you entered long at 4500, price dipped to 4493 before recovering and you exited at 4510, the MAE was 7 points. Like MFE, it's a fixed property of the price path during the trade, independent of the final outcome.

MAE is the lower boundary of the intra-trade envelope — the deepest the trade went underwater before resolving. It tells you how much heat the trade took, regardless of whether it ultimately worked.

The reason MAE matters as a tracked statistic is that the realised outcome of a trade doesn't reveal how close it came to failing. A +10 point winner that briefly dipped to −8 is a very different trade from a +10 winner that never went negative — same P&L, very different risk-of-ruin profile.

Why it matters

MAE is the diagnostic for stop placement and trade survival. Specifically:

• Low MAE on losers signals that your stops are doing what they're supposed to — the trade got stopped out because the thesis broke, not because of noise.
• Low MAE on winners signals tight winners that didn't go offside before working. Strong setup quality.
• High MAE on winners signals trades that took significant heat before recovering — survivable in retrospect, but path-dependent and stressful.
• High MAE on losers near the stop signals that price approached the stop, recovered, then came back and took it out — a classic noise-pattern problem.

Aggregated across many trades, MAE distributions inform whether stops are placed inside or outside the normal noise envelope of the instrument. A well-calibrated stop sits beyond typical MAE on winners but inside typical price excursion on losers.

How traders use it on Sierra Chart

MAE, like MFE, is a post-trade analytic that requires reconstructing the price path during each trade's hold from tick data. Live order entry doesn't surface it; it's computed after the fact from the actual ticks during the position's lifetime.

The SCS Trading Journal computes MAE per trade by reading Sierra Chart's SCID tick files, so the metric is grounded in real intra-trade price action. The journal surfaces MAE distributions per strategy, MAE-vs-realised plots, and MAE vs stop-distance comparisons that show how often trades approached the stop without triggering it.

For analysing whether a stop is too tight or too loose, the MAE distribution on winners is one of the most direct inputs available.

Common patterns / pitfalls

• MAE estimated from minute bars systematically underreports the true depth — use tick-level data for accurate measurement.
• A high MAE on winners isn't automatically bad. Some strategies (mean reversion, fade) intentionally enter into adverse moves and rely on a wider envelope.
• A pattern of losing trades whose MAE was just past the stop signals stops placed inside the instrument's noise band. The fix is on the stop side, not the entry.
• MAE on partial-exit trades is fuzzy. Pick a convention (typically: MAE of the original full position) and stick to it.
• Don't optimise stop placement to minimise MAE in isolation. Wider stops reduce MAE on winners but inflate per-trade risk — the trade-off cuts both ways.

Related SCS studies

Trading Journal computes MAE per trade from Sierra Chart's tick files automatically, surfacing distributions alongside MFE so stop placement and trade-survival quality can be measured against the actual price path of each hold.