Analytics Labs — MAE/MFE Lab

What happened between entry and exit is the story.

The formula family

Six numbers that grade every trade.

Straight from the lab's formula reference:

MAE R — worst unrealized drawdown of the trade; Adverse Utilization = |MAE R| shows how much of the stop was consumed.
MFE R — highest unrealized profit before close; opportunity generation.
Capture Efficiency = MAX(0, Outcome R) ÷ MFE R — how much of the available move was actually kept.
Giveback R = MAX(0, MFE R − Outcome R) — open profit surrendered before exit.
Fee R Drag = Total Fees ÷ Risk $ — how much of 1R costs consumed.
Net Outcome R = Outcome R − Fee R Drag — the realistic result after friction.

The formula family

Six numbers that grade every trade.

Straight from the lab's formula reference:

01MAE R — worst unrealized drawdown of the trade; Adverse Utilization = |MAE R| shows how much of the stop was consumed.

02MFE R — highest unrealized profit before close; opportunity generation.

03Capture Efficiency = MAX(0, Outcome R) ÷ MFE R — how much of the available move was actually kept.

04Giveback R = MAX(0, MFE R − Outcome R) — open profit surrendered before exit.

05Fee R Drag = Total Fees ÷ Risk $ — how much of 1R costs consumed.

06Net Outcome R = Outcome R − Fee R Drag — the realistic result after friction.

The core idea

How MARS uses this

Each closed trade logs its worst adverse excursion and best favorable excursion. The lab plots them into quadrants and pairs the picture with capture efficiency, giveback, and fee drag - then the EV Driver Diagnostics rank which repair (entry location, coefficient, trail logic, cost avoidance) would move net expectancy most.

How it benefits you

Review produces one concrete fix instead of a vague resolution to 'trade better'. You see whether stops are too tight, entries are chased, exits leak the runner, or fees quietly eat the edge - and whether a profitable week was actually clean or just lucky.

Every trade plotted by pain taken (MAE) versus opportunity generated (MFE). The four quadrants diagnose entry precision and exit management at a glance.

Branch-aware judgment

Four branches, four different 'good'.

Normal should show stable excursions and high capture. Trend Partial with good MFE but poor capture means the trail is leaking the runner. Trend No-Partial with low MFE and high MAE isn't earning its variance. Overflow with high fee drag or swap damage has become hidden recovery trading. One generic standard would misjudge all four.

The repair engine

EV Driver Diagnostics and What-If.

The lab's driver diagnostics rank MAE pressure, MFE opportunity, capture, giveback, adverse utilization, fee drag, and adherence against targets — flagging DRAG/WATCH states. The What-If Scenario Engine then estimates which single repair would move net EV most, so review produces one concrete fix instead of a vague resolution to 'trade better'.

Inside this module

3 pages go deeper than this one.

The Formula Family

Go deeper →

Branch-Aware Judgment

Go deeper →

The Repair Engine

Go deeper →

Connected inside MARS

This module doesn't work alone.

Connected — 01

Trade Lifecycle

Open system page →

Connected — 02

Variant Attribution

Open system page →

Connected — 03

Monetization Efficiency Ratio

Open system page →

Use cases

Where it earns its place

▸Diagnosing whether stops are too tight (high MAE trades that eventually work) or entries are chased
▸Detecting exit leakage: high MFE with low capture and rising giveback
▸Quantifying fee and swap drag that gross R hides
▸Auditing whether a profitable week was actually clean

Edge cases & failure modes

Where it can mislead

!Judging all branches with one standard — TNP's variance profile is not Normal's failure.
!Overreacting to one or two trades per timeframe bucket; sample size gates every read.
!Optimizing capture so hard that trend branches get choked — capture and giveback trade off against continuation room.

Go deeper

Operator briefs on this territory.

Deep dive — 01

MAE/MFE: what your trades did while you weren't looking.

Reading maximum adverse and favorable excursion to audit stops, targets, and exits with evidence.

Read the full brief →

Deep dive — 02

Capture and giveback: grading the exit against what the trade offered.

MFE is what the market offered. Outcome is what you kept. The gap has a name, and it compounds.

Read the full brief →

Deep dive — 03

Reading execution evidence: the scenarios that fool operators.

Profitable isn't clean. Red isn't broken. The label isn't the behavior. The scenario guide, walked.

Read the full brief →

Take it further

Capture and giveback respond sharply to stop and trail choices. The Foundry lets you replay a record under different management assumptions rather than trading your way to the answer.

Open the AlphaRail Foundry Lab ↗

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