Execution Risk Profile
Execution Precision
8 min read
Build your personal execution risk profile to understand your strengths, weaknesses, and optimal risk parameters.
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8 min read
Build your personal execution risk profile to understand your strengths, weaknesses, and optimal risk parameters.
Your strategy has an edge — but your execution style has a personality. Learn to trade like the version of you that wins consistently.
An execution risk profile is a quantified document that captures, per setup, a trader's stop-distance distribution, killzone expectancy, MAE/MFE percentiles, BE-trigger fill rate, and rule-adherence score. It converts personality into parameters. Build one only after 50+ logged trades per setup — anything less and you are codifying noise as rules.
This lesson is the capstone of the Stop Placement module. Every prior lesson contributed one input. The profile fuses those inputs into a single executable document you re-derive every 100 trades.
You arrived here with seven prior lessons in your kit. The profile is not new content — it is the integration layer.
The profile is a single page that tells you which six-to-ten numbers from those lessons are yours, and what rules drop out of those numbers.
A 0.4-edge system you execute with 95% adherence beats a 0.6-edge system you execute at 60%. Personalizing the profile is not about comfort — it is about closing the rule-adherence gap. Measure adherence first; if it is already above 90%, do not personalize. Hold the line and scale size instead.
Two failure modes to avoid before you build:
Self-report is biased. Pull from your last 50+ logged trades and compute six numbers:
| # | Dimension | Where it comes from |
|---|---|---|
| 1 | Median MAE in R | MAE/MFE lesson |
| 2 | 75th-percentile MAE in R | MAE/MFE lesson |
| 3 | Win-rate by killzone | Killzones lesson |
| 4 | Expectancy (R) by setup tag | Journal — group by your tag column |
| 5 | Average time-in-trade, winners vs losers | Journal — exit_ts - entry_ts, split by outcome |
| 6 | BE-stop hit-rate | Moving to Break-Even |
| Dimension | Self-report version | Journal-derived version | Why journal wins |
|---|---|---|---|
| Stop preference | "I prefer tight stops" | Median MAE = 0.7R, 75th-pct = 1.3R | Self-report ignores the trades where you widened mid-flight |
| Entry style | "I'm mostly a limit trader" | 64% market, 31% limit, 5% stop-entry | Slippage cost is invisible without the breakdown |
| BE behavior | "I move to BE quickly" | BE-stop hit-rate = 41% | Quick BE moves leak edge if hit-rate exceeds ~30% |
| Cut-early frequency | "I rarely cut early" | 22% of stopped trades closed manually before stop hit | The narrative you tell yourself is not the data |
| Emotional trigger | "Boredom" | 80% of off-plan entries fall in the 11:00–13:00 UTC dead zone | Time-stamps surface the real trigger |
You now have your natural style as a vector of numbers. Optimize within it.
This is what a populated profile looks like. Use it as a template, not a target.
Central tendency of run-against across the 73-trade sample.
Stop-sizing anchor. Stops sized to this percentile capture three-quarters of the historical adverse excursion.
Prime London window where the sample trader's expectancy concentrates.
Expectancy collapse window. Drives the no-new-entries-after-11:00-UTC derived rule.
Winners typically resolve faster than this; informs the time-stop overlay.
Losers die quickly. Trades that linger past this mark without progress are usually losers in slow motion.
Frequency of trades stopped out exactly at break-even. Above roughly 30 percent indicates premature defense is leaking edge.
Win-rate by session window (London breakout sample, n=73)
Expectancy collapse after 11:00 UTC justifies the no-new-entries-after-11:00-UTC derived rule.
Derived rules (drop out of the numbers):
| Dimension | Tight-stop scalper | Wide-stop swing |
|---|---|---|
| Median MAE | 0.4R | 1.1R |
| 75th-pct MAE | 0.8R | 1.8R |
| Avg time-in-trade | 6 min | 4.5 hours |
| Preferred killzone | NY-AM open | London-NY overlap |
| BE trigger | 0.6R or first higher low | 1.5R or HTF structure |
| Daily trade cap | 8 | 2 |
| R-target | 1.5R median | 4R median |
Two valid systems. Same instrument. Different profiles. Neither is correct in isolation — each is correct for the trader whose journal produced it.
| Trade phase | Action / rule (fill from your numbers) |
|---|---|
| Entry trigger | (e.g. BOS + imbalance reclaim only) |
| Stop logic | Structural stop, sized to your 75th-pct MAE |
| BE logic | After [your BE-trigger threshold] R + structural confirmation |
| Management | Hold/reduce/bail per Real-Time Trade Management |
| Exit logic | Full TP at [your median R-target] or structural break |
Overlays to consider:
A capstone should produce a harder artifact than the lessons it integrates. Populate this matrix from your data — every cell holds three values: (stop multiple, target R, max hold).
| Killzone | Trend setup | Range setup | News setup |
|---|---|---|---|
| London (07:00–10:00 UTC) | (1.4× ATR, 3R, 60m) | (1.0× ATR, 1.5R, 30m) | skip |
| NY-AM (13:00–15:00 UTC) | (1.6× ATR, 4R, 90m) | (1.2× ATR, 2R, 45m) | (2.0× ATR, 2R, 20m) |
| NY-PM (15:00–20:00 UTC) | (1.8× ATR, 4R, 120m) | skip | skip |
If a cell does not have at least 20 trades behind it, write insufficient data and do not trade it.
Unanchored 1–5 scores are noise. Each row needs concrete language so a 3 today equals a 3 next month.
Anchored execution-scoring rubric: each numeric anchor (5, 3, 1) is described by a behavioral phrase so scores are stable across time and traders.
| Category | 5 (anchor) | 3 (anchor) | 1 (anchor) |
|---|---|---|---|
| Plan followed | Entry, stop, target matched written plan exactly | One parameter drifted under 20 percent from plan | Discretionary trade with no pre-written plan |
| Entry timing | Filled at intended trigger plus or minus 1 tick, no chasing | Chased under 0.2R past trigger | Chased over 0.5R or jumped trigger by over 1 bar |
| Stop placement | Stop sized to MAE percentile, anchored to structure | Stop sized correctly but anchored to round number | Stop sized by gut |
| Emotional control | Held plan through draw-down at or below 75th-pct MAE | Felt pressure, did not act on it | Manual closure or size change driven by emotion |
| Exit discipline | Exited at target or rule-based invalidation | Exited 1 bar early or late, plan substantially honored | Exited on noise, target moved mid-trade |
02-Apr ES short, –0.8R loss. Plan = 5 (rule-set entry on BOS + retest), Entry = 4 (filled 1 tick late), Stop = 5 (at structural high, 1.4× ATR), Emotion = 5 (held through 0.6R draw-down without touching mouse), Exit = 4 (stopped at level, exit price 1 tick worse than stop). Composite = 4.6. The loss is banked; the execution is repeatable.
Compare to 03-Apr ES long, +1.2R win. Plan = 2 (no setup match, jumped on momentum), Entry = 1 (chased 0.4R), Stop = 3 (round number, not structure), Emotion = 1 (pressed because of prior loss), Exit = 3 (closed early on noise). Composite = 2.0. Profitable but unrepeatable — you cannot trade like that for 100 reps and survive.
A trade that loses money but scores 5s is your edge running correctly. A trade that wins money on a 2 is variance hiding behavior you must extinguish.
A profile is a snapshot, not a constitution. Refresh it on any of:
A profile built in trending Q1 will mislead you in choppy Q3. Date every profile and keep the prior version in your journal so you can compare derived rules across regimes.
| Phase | Action | Measurable output | Pass criterion |
|---|---|---|---|
| Pre-session | Define bias, mark POIs, set greenlight checklist, review setup MAE/MFE | Written plan with 5+ tagged setups | All entries today must match a tagged setup |
| Pre-session | Review current 30-trade rolling MAE percentile | Number on the journal page | Stop sizing today uses this number, not last month's |
| During session | Take only planned triggers; no unplanned entries | Off-plan entry count | 0 |
| During session | Manage with hold/reduce/bail per Real-Time Trade Management | Manual interventions logged | Each intervention rule-justified in journal field |
| Post-session | Score every trade against the rubric | Composite score per trade | Daily rolling avg ≥ 4.0 |
| Post-session | Note breakdowns, emotional cues, rule changes proposed | Tagged journal entries | Each rule change requires 30+ trade evidence before adoption |
This is how professionals trade the same playbook day after day — but adapt parameters to the day's environment without abandoning the system.
An execution risk profile is a quantified document that, per setup, captures a trader's stop-distance distribution, killzone expectancy, MAE/MFE percentiles, BE-trigger fill rate, and rule-adherence score. It converts personality into parameters and is built from 50+ logged trades, not memory.
Each dimension needs at least 30 trades for the answer to mean more than chance, and at least 50 before you would risk capital on the derived rule. Below 50 trades per setup tag, variance dominates the signal and you will codify noise.
Score five categories — plan followed, entry timing, stop placement, emotional control, exit discipline — on a 1–5 scale with anchored behavioral descriptors. A 5 is "matched written plan exactly", a 3 is "one parameter drifted <20%", a 1 is "discretionary, no plan". Composite is the unweighted mean.
A trade that loses money but scores all 5s on the rubric. The loss is banked, the process is repeatable, and over enough reps the edge expresses itself. A profitable trade scoring 2s is variance hiding behavior you must extinguish.
Refresh every 100 trades, after any regime change (volatility shift, new instrument, new session), or after 20 consecutive trades that score above 4 but lose money. A profile is a snapshot, not a constitution.
Your edge is the gap between your written rules and your clicks. Profile that gap monthly. The trader who shrinks it 5% per quarter compounds faster than the one chasing a better signal.
Next, automate any rule that survives 100 trades using Smart Stops, or move into Module 5: Scaling & Exit Execution.