MAE and MFE: the two numbers that describe a trade's whole life.

The two excursions

Adverse and favorable, both in R.

MAE — maximum adverse excursion — is the deepest open-trade drawdown before close, expressed in R units, and it diagnoses entry timing, stop quality, and noise tolerance. MFE — maximum favorable excursion — is the highest unrealized profit the position reached, diagnosing opportunity generation and exit efficiency. Recording both in R rather than price makes them comparable across pairs, timeframes, and position sizes, and the lab's pip translation exists to confirm the R accounting reconciles with actual market distance. From these two primitives, every efficiency metric in the lab derives: capture, giveback, adverse utilization, the MFE/MAE ratio, and the stop efficiency score.

The derived reads

Four ratios, each answering a different execution question.

Adverse utilization is the absolute value of MAE — how much of the original stop risk the trade actually consumed, which is the cleanest read on whether stops are sized for the noise they're meant to survive. The MFE/MAE ratio is reward opportunity relative to pain taken, a per-trade read on whether the setups being selected offer enough upside for the heat they demand. Capture efficiency and giveback grade the exit against the opportunity. And stop efficiency scores whether the stop placement was structurally sound in hindsight. Each is a different slice of the same path, which is why the lab computes them together rather than letting any single one stand as the verdict on a trade.

The combination reads

MAE and MFE together produce four distinct diagnoses.

The lab's operator reading rules turn the pair into a quadrant. Low MAE with high MFE is the clean profile — precise entries generating real opportunity, and the only remaining question is whether the exit captured it. High MAE with high MFE says the thesis was right but the entry was early or the stop tight against the structure's actual noise: the trades work, and they cost more heat than they should. Low MAE with low MFE describes trades that never developed — often a selectivity or regime-fit issue rather than an execution one. And high MAE with low MFE is the worst profile: maximum pain for minimum opportunity, which usually indicts setup quality or regime misclassification rather than management.

• MAE is an entry and stop diagnostic; MFE is an opportunity and exit diagnostic. Don't let one answer the other's question.
• Both are recorded from the actual price path — never inferred from the outcome, which would make every read circular.
• Duration sits alongside them: the same excursion profile means different things over twenty minutes and two days.

The classification layer

From raw excursions to graded output.

The lab doesn't stop at ratios. Its output classifications convert them into readable states — MAE quality, MFE quality, an efficiency zone, a pips-translation check, an execution grade, a branch integrity flag, and a data QA status. Those classifications are what make weekly rollups possible: high-MAE counts, elite-MFE counts, breakeven trigger rates, and week quality grades all aggregate from per-trade classifications rather than raw numbers. The branch integrity flag deserves particular note — it's the automated version of the branch-mismatch scenario, surfacing trades whose behavior didn't match their declared branch so the classification can be examined rather than quietly absorbed.

The key idea

A result is a point; a path is evidence.

Two trades closing at identical R can have lived completely different lives — one gliding to target, the other surviving a near-stop and surrendering most of a large excursion. Outcome-only records treat them as the same evidence, which means execution quality is invisible in the very data meant to measure the system. MAE and MFE restore the dimension, and everything the efficiency layer knows is built from that restoration.