Two traders take the identical setup and both book a winner, but one grabbed most of the move and the other a sliver. On the P&L they look similar; underneath, one has a durable process and the other is leaving the edge on the table. Efficiency metrics make that invisible gap measurable.
The efficiency idea: captured vs available move
Every trade offers a range of price while you’re in it. Two excursions define that range:
- MAE — Maximum Adverse Excursion: the worst unrealized loss the trade reached against you before you closed.
- MFE — Maximum Favorable Excursion: the best unrealized profit the trade reached in your favor.
Efficiency asks a simple question: of the move that was available, how much did you actually capture? A profitable trade that only banked a fraction of a large favorable swing was inefficient even though it won. A losing trade you exited near its best available point was, in a real sense, well managed. Efficiency separates the quality of your decisions from the luck of the outcome — which is exactly what you want to grade if you plan to repeat the process a few thousand times.
Log MAE and MFE in the same units you risk in. Working in R-multiples keeps trades comparable across instruments and account sizes; if that framing is new, start with the r-multiple primer.
Entry efficiency from MAE
Entry efficiency measures how well-timed your entry was, using MAE as the yardstick. The intuition: a good entry doesn’t go far underwater before it works. If a trade immediately sags most of the way to your stop before recovering, your timing was poor even if it ultimately won.
A clean way to score it against the trade’s full range is:
entry efficiency = MFE / (MFE + MAE)When the adverse heat is small relative to the favorable move, the score climbs toward 1; when a trade drags deep against you before it pays, it falls. Track the distribution, not one trade: persistently large MAE on winners is the signature of entering early — chasing before confirmation, or fading into strength. It has two costs. It inflates the stop distance you need, worsening your risk-reward, and it makes trades psychologically harder to hold because they hurt before they help.
Exit efficiency from MFE
Exit efficiency is the one most discretionary traders fail. It compares what you booked against the MFE — the best the trade ever offered:
exit efficiency = realized_gain / MFEIf a trade ran to +3R (MFE) and you closed at +1R, your exit efficiency was about 33% — you captured a third of what the trade gave you. Score it per trade, then look at the distribution:
- Consistently low exit efficiency = cutting winners short, usually from fear of giving back profit.
- Exit efficiency near or above a healthy band, trade after trade, = a repeatable exit process.
A subtlety: 100% exit efficiency every time is not the goal and usually signals hindsight bias in how you’re measuring. No one nails the tick. The aim is a stable, high band across many trades — evidence that your exit rule, not luck, is doing the work.
Total efficiency and what good looks like
Total efficiency blends the two into a single grade for the whole trade — roughly, how much of the entry-to-MFE potential you converted into realized profit. It’s the honest headline metric, but the components are where the diagnosis lives.
| Pattern | Entry eff. | Exit eff. | Likely problem |
|---|---|---|---|
| Wins but small | High | Low | Cutting winners short |
| Painful winners | Low | High | Entering too early / chasing |
| Death by a thousand cuts | Low | Low | Setup or timing is off |
| Clean process | High | High | Refine size, not mechanics |
Don’t chase a magic percentage. “Good” is stable and improving on your own baseline, measured over a meaningful sample. A single trade’s efficiency is noise; the distribution across a hundred is signal.
Diagnosing early entries vs late exits
The power of splitting entry from exit is that it points to different fixes:
- Low entry efficiency (large MAE on winners) → your trigger is too eager. Wait for confirmation, tighten the setup definition, or enter in stages so the average price sits closer to the turn.
- Low exit efficiency (leaving MFE behind) → your management is too eager. A trailing stop, a partial-scale rule, or a defined target based on structure will capture more of what’s already there.
- Both low → the setup itself may not have an edge worth trading. Efficiency is telling you to fix the strategy, not the execution.
Reading these patterns requires clean, granular trade data — every fill, the actual MAE and MFE, the timestamps. That’s tedious by hand and nearly impossible to reconstruct honestly after the fact. Shibiki auto-journals every trade straight from the broker, so MAE/MFE and efficiency are computed from real fills rather than remembered ones. On the futures side, that pipe runs through connectors like Tradovate and ProjectX, which stream the execution detail these metrics depend on.
Turning efficiency scores into rule tweaks
Metrics only matter if they change what you do next. A tight loop:
- Segment your efficiency scores by setup, session, and instrument — the leak is rarely uniform.
- Isolate one lever. If exit efficiency is dragging, test one exit rule change (a trailing stop, a partial at a fixed R) and hold everything else constant.
- Re-measure on fresh trades before deciding. One good week proves nothing; a shift in the distribution across a sample does.
- Watch the edge, not just the metric. A management change that lifts exit efficiency but lowers overall expectancy is a bad trade for a good number.
That last point is the guardrail. Shibiki tracks live edge health per strategy with a Wilson confidence interval, so when you tune an exit rule you can see whether the strategy’s real edge moved or whether you just optimized a vanity stat. Efficiency tells you where the leak is; the edge metric confirms the patch actually held. Before you widen a target chasing MFE, sanity-check the trade math on the risk-reward calculator so a prettier efficiency score doesn’t quietly wreck your reward-to-risk.
Related: R-multiple · Risk-reward calculator · Tradovate integration