Post-Trade Execution Review
Execution Precision
8 min read
Evaluate execution quality by comparing actual fills against theoretical prices at the time of signal generation.
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8 min read
Evaluate execution quality by comparing actual fills against theoretical prices at the time of signal generation.
The trade does not end at the exit. What you measure after the fill determines whether the next 100 trades will be better or worse than the last 100.
Post-trade execution review (the retail subset of institutional Transaction Cost Analysis or TCA) compares your actual fills against the price available at the moment your signal fired. It scores process quality independently of P&L. It produces measurable improvement targets, not narratives.
Most traders review their trades to answer one question: "Did I make money?" This is the least useful question you can ask. A winning trade executed poorly teaches you bad habits. A losing trade executed perfectly confirms your edge is working.
Post-trade execution review shifts the focus from outcomes to process. It measures how well you translated your plan into action -- independent of whether the market cooperated. Over time, this is what separates traders who improve from traders who repeat the same mistakes for years.
Every trade can be evaluated across four independent dimensions. A complete review scores each one separately, because a trade can have excellent signal quality and terrible exit execution, or poor entry timing but perfect trade management.
Did the setup meet your predefined criteria at the moment you took the trade?
| Question | Score Range |
|---|---|
| Did the setup match a defined pattern in your playbook? | 0 - 3 |
| Was the market context aligned (trend, volume, volatility)? | 0 - 2 |
| Were there any disqualifying factors you ignored? | 0 or -2 |
Maximum signal score: 5
A signal score of 3 or below means the trade should not have been taken. Track how many sub-3 trades you take per week. If it is more than 20% of your total trades, your filtering discipline is the primary problem -- not your execution.
How well did you execute the entry once you decided to take the trade?
| Question | Score Range |
|---|---|
| Was the entry within your planned price zone? | 0 - 2 |
| Did you use the correct order type for the situation? | 0 - 1 |
| Was execution timely (within your latency threshold)? | 0 - 1 |
| Was position size calculated correctly? | 0 - 1 |
Maximum entry score: 5
Entry quality is where slippage lives. The benchmark you compare against is the arrival price -- the mid quote at the moment your signal fired. Fill minus arrival, in basis points, is your implementation shortfall on the entry leg. Above 5 bps on BTC/USDT at retail size means your routing, latency, or order type is leaking edge -- not the market.
At retail size you cannot move the market, but you can lose to it consistently. 5 bps per side, 200 round-trips per year, equals 200 bps -- 2% drag annually. That is the difference between an edge and a hobby.
5 bps x 2 sides x 200 round-trips per year = 200 bps. The difference between an edge and a hobby.
How well did you manage the position between entry and exit?
| Question | Score Range |
|---|---|
| Did you follow your stop management rules? | 0 - 2 |
| Did you avoid moving your stop closer out of fear? | 0 - 1 |
| Did you follow your partial profit-taking plan? | 0 - 1 |
| Did you avoid adding to losers or revenge sizing? | 0 - 1 |
Maximum management score: 5
Management quality is the dimension most affected by psychology. A common pattern: management scores are high during the first 3 trades of the day and decline steadily after losses. If you see this in your data, it is a fatigue or tilt signal.
How well did you execute the exit?
| Question | Score Range |
|---|---|
| Did you exit for a reason in your plan (not emotion)? | 0 - 2 |
| Was the exit order type appropriate? | 0 - 1 |
| What was the MFE Capture Ratio? (above 0.60 = full marks) | 0 - 2 |
Maximum exit score: 5
If you trade perpetuals, add a fifth quiet line item: funding paid while in position. A 0.05% funding rate paid every 8 hours over a 36-hour hold is 22.5 bps -- larger than your slippage budget.
0.05% x (36h / 8h) = 0.05% x 4.5 = 22.5 bps
This is a process scorecard, not a transaction cost analysis. TCA -- arrival-price slippage, VWAP comparison, market impact, participation rate -- lives inside the Entry and Exit dimensions above. The scorecard wraps cost data with discipline data so a single number flags both kinds of leak.
Combine the four dimensions into a single per-trade scorecard:
Execution Score = Signal Quality + Entry Quality + Management Quality + Exit Quality
Maximum: 20 points
| Score | Verdict | Action |
|---|---|---|
| Above 16 | Excellent execution | Continue process regardless of P&L outcome |
| 12 - 16 | Solid execution | Identify one dimension to improve |
| 8 - 12 | Significant issues | Diagnose weakest dimension before next trade |
| Below 8 | Execution breakdown | Stop trading; review setup adherence before resuming |
The Implementation Shortfall lesson later in this module formalizes the entry/exit cost components into the institutional TCA framework -- the same math, named for the literature.
The entire point of the scorecard is to decouple execution quality from trade outcome. A losing trade can score 18/20 (you did everything right, the market did not cooperate). A winning trade can score 9/20 (you got lucky despite poor execution). Over 100+ trades, high execution scores correlate with positive expectancy. Low scores correlate with negative expectancy regardless of short-term results.
Use this template after every trade. Capture signal price via TradingView alert webhook (exports timestamp + price to a Google Sheet or n8n). Capture fill price via exchange API (Binance, Bybit, OKX all expose a fills endpoint). Reconcile the two columns. Two minutes per trade, ten minutes per month for the pivot. The discipline of completing it is itself a performance improvement tool.
| Field | Example (BTC/USDT Long) |
|---|---|
| Date and time | 2024-03-15 14:32 UTC |
| Setup type | Order block reclaim, bullish |
| Signal price (arrival) | $67,380 |
| Fill price | $67,405 |
| Entry slippage | 3.7 bps = (67405 - 67380) / 67380 * 10000 |
| Stop level | $66,900 |
| Target level(s) | $68,200 / $68,800 |
| MAE | 0.35R ($67,230) |
| MFE | 2.8R ($68,720) |
| Exit price | $68,145 |
| MFE Capture Ratio | 0.58 |
| R-Multiple result | +1.54R |
| Signal score | 4/5 |
| Entry score | 4/5 |
| Management score | 3/5 |
| Exit score | 2/5 |
| Total execution score | 13/20 |
| Notes | Exited too early, feared reversal at round number. MFE continued 1.2R beyond exit. |
Good signal and entry, but exit was premature. MFE reached $68,720 (2.8R) but exited at $68,145 (1.54R). Management score dragged down by moving partial TP closer during consolidation.
This trade illustrates how a winning trade can still reveal execution problems. The 0.58 MFE Capture Ratio means 42% of the available move was left on the table -- primarily due to fear-based exit timing rather than slippage.
Individual reviews are useful. But the real power emerges when you analyze patterns across 50, 100, or 200 reviews. Run these analyses monthly:
Calculate your average score for each dimension over the review period:
| Dimension | Threshold | Diagnosis |
|---|---|---|
| Signal Quality | Avg < 3.5 | Taking too many low-quality setups -- filtering discipline |
| Entry Quality | Avg < 3.5 | Execution process needs automation or refinement |
| Management Quality | Avg < 3.5 | Discipline or psychology issue |
| Exit Quality | Avg < 3.5 | Exit rules unclear or being overridden |
Plot execution scores by session (Asia, Europe, US). Many traders discover their scores drop significantly during specific sessions due to fatigue, overtrading, or unfavorable liquidity conditions.
Plot execution scores by trade number within the day (1st trade, 2nd trade, 3rd trade, etc.). A declining score after the 3rd trade is one of the most common patterns. It suggests a hard daily trade limit would improve overall performance.
Compare average execution scores for winning trades vs losing trades. If winners and losers have similar execution scores, your process is consistent and outcomes are driven by market randomness -- which is exactly what you want. If losers have significantly lower scores, execution breakdowns are causing losses rather than normal variance.
Data without action is just record-keeping. Each monthly review should produce exactly one or two specific, measurable improvement targets for the next period.
| Pattern Found | Improvement Target | Measurement |
|---|---|---|
| Exit scores drop after 2nd trade | Implement mandatory 15-minute break after 2nd trade | Track exit score for trade 3+ next month |
| Entry slippage above 5 bps during US open | Switch to limit orders during 13:30-14:30 UTC | Measure entry slippage for that window |
| MFE Capture Ratio below 0.50 on trend trades | Implement trailing stop at 0.5R intervals instead of fixed TP | Compare capture ratio month over month |
| Signal scores below 3 on 25% of trades | Add a pre-trade checklist with 3 mandatory confirmations | Track percentage of sub-3 signal scores |
Do not attempt to fix three execution problems simultaneously. Changing multiple variables at once makes it impossible to determine which change helped. Pick the single highest-impact improvement, implement it for 30+ trades, measure the result, then move to the next one.
Because outcome and process are not the same edge. A losing trade can score 18/20 and a winning trade can score 9/20. Over 100+ trades, high execution scores correlate with positive expectancy and low scores correlate with negative expectancy regardless of short-term results.
Signal quality, entry quality, management quality, and exit quality. Each is scored 0-5 and summed into a 20-point execution score. The dimensions are independent: a trade can have excellent signal quality and terrible exit execution, or poor entry timing but perfect trade management.
Two to three minutes per trade if the template fields are pre-defined. Capture is automatable -- TradingView webhook for signal price, exchange API for fill price -- so the manual portion is scoring the four dimensions and writing one note line.