Execution quality monitor: slippage, spread, rejects, and fills
Measure the difference between planned and actual execution so strategy results include spread, slippage, rejects, requotes, and partial fills.
Lesson outcomes
- Create an execution-quality log for manual trades, EAs, and copiers.
- Separate strategy logic errors from broker/execution conditions.
- Use execution data to decide when to pause a strategy.
Workshop lab
Complete the demo, notebook, platform, or code task before treating the lesson as finished.
Evidence pack
Keep screenshots, exports, logs, calculations, or code versions in a dated learning folder.
Pass standard
You should be able to explain the failure modes, show your work, and name the stop rule.
Free education, not signals. This lesson is part of EarnSouthAfrica's free forex course. It does not tell you what to buy or sell, it does not promise income, and it should be practised on a demo account before any real-money decision.
Backtests often assume cleaner execution than real accounts experience. Even on demo, learners should measure requested price, filled price, spread, reject reason, and latency context. This is how they stop blaming charts for execution problems or ignoring costs when results look good.
This lesson builds a small execution-quality database concept that can live in CSV logs, journal exports, or a later dashboard.
What you should be able to do after this lesson
- Create an execution-quality log for manual trades, EAs, and copiers.
- Separate strategy logic errors from broker/execution conditions.
- Use execution data to decide when to pause a strategy.
Execution fields
| Field | Reason |
|---|---|
| Requested price and filled price | Measures slippage and price improvement/deterioration. |
| Spread before request | Shows whether cost was abnormal at entry or exit. |
| Retcode and comment | Explains accepted, rejected, delayed, or modified outcomes. |
| Event context | Session, news window, rollover, VPS status, and connection state. |
Quality thresholds
- Pause entries when spread exceeds the strategy's cost assumption.
- Reject trade classes with repeated retcodes that indicate invalid stops, disabled trading, or margin pressure.
- Flag symbols whose average slippage is worse than the backtest assumption.
- Review copier performance separately for provider fill, receiver fill, and follower slippage.
Review dashboard
A simple dashboard should show average spread, worst spread, average slippage, rejected orders by reason, fills by session, and performance after costs. A beautiful equity curve without execution-quality context is incomplete evidence.
Academy-grade study plan
This is the production-thinking layer of the course. A serious MT5 system is not a lucky Expert Advisor; it is a documented machine with account preflight, symbol preflight, event handling, risk gates, order checks, logs, recovery rules, and demo evidence for every assumption.
| Course element | What you must produce |
|---|---|
| Primary artifact | EA systems engineering dossier |
| Lesson focus | Execution quality monitor: slippage, spread, rejects, and fills |
| Working environment | Demo account, notebook, exported platform data, or local code sandbox. Never live funds for first practice. |
| Completion standard | You can explain the concept, reproduce the exercise, identify failure modes, and show evidence without relying on a seller's claims. |
Instructor workflow
Use this workflow as if an instructor were marking the lesson. The important question is not whether the topic sounds familiar. The question is whether your notes, screenshots, calculations, logs, or code prove that you can apply execution quality monitor: slippage, spread, rejects, and fills under controlled conditions.
- Start every system session by recording account mode, margin mode, symbol specification, trade permissions, spread state, stops level, freeze level, and session/news context.
- Separate signal logic, position sizing, preflight checks, order submission, trade lifecycle tracking, recovery, and observability so failures can be isolated.
- Use MT5 and MQL5 events deliberately: OnTick for market updates, OnTimer for scheduled checks, OnTradeTransaction for lifecycle evidence, and OnBookEvent only when market-book data is subscribed and useful.
- Treat every reject, retcode, skipped trade, stale quote, bad tick, and risk block as useful evidence rather than an annoyance.
Worked case study: The EA refuses to trade for the right reason
A learner runs a demo EA during a volatile session. The signal is true, but the symbol has a widened spread, the requested stop is inside the broker's stop level, and margin would be too tight after the order. A weak bot sends the trade and blames the broker. A professional system logs each preflight result, rejects the order before submission, and records the account state for review.
After reading the scenario, write the decision you would make before checking the suggested workflow above. Then compare your decision with the operating model. The gap between those two answers is the part of the lesson that deserves another demo repetition.
Professional template
Complete this template in your own notebook. A paid course would normally hide this kind of operating document behind worksheets; here it is part of the free lesson.
| Field | Standard |
|---|---|
| Preflight area | Account mode, symbol specification, margin, stops/freeze level, spread, session, and permission state. |
| Event handler | OnTick, OnTimer, OnTradeTransaction, OnBookEvent, OnCalculate, or OnTester responsibility. |
| Safety gate | The exact condition that blocks duplicated, oversized, stale, unfillable, or undocumented trades. |
| Evidence | Journal/Experts log, tester report, exported settings, screenshots, retcode notes, and review memo. |
Failure-mode lab
Paid courses often sell confidence. A serious course teaches you how the idea breaks. Before continuing, test the failure modes below on demo, paper, or code review. If you cannot describe the failure, you are not ready to trust the concept.
- Sending orders before checking broker symbol rules, account mode, filling policy, margin, and stop-distance constraints.
- Using OnTick for every responsibility until the EA becomes impossible to debug.
- Ignoring trade-server retcodes, partial fills, rejects, and asynchronous lifecycle events.
- Optimizing parameters while the underlying execution and risk engine is still unproven.
Evidence pack and pass standard
Do not mark this lesson complete because you read it. Mark it complete only when you can show the evidence below. Keep the files in a dated folder so your learning history survives platform updates, memory gaps, and sales pressure.
- A one-page note explaining execution quality monitor: slippage, spread, rejects, and fills without sales language or copied definitions.
- A screenshot, export, calculation, log, or code file that proves the practical work was completed on demo.
- A written stop rule that says when this topic must not be used with real money.
- A system preflight table showing pass/fail results for at least three symbols on demo.
- A log excerpt where the system rejects a tempting but unsafe trade with a clear reason.
Assessment rubric
| Level | What it looks like |
|---|---|
| Not ready | You can repeat the vocabulary but cannot complete the demo task, calculate the risk, explain the failure mode, or show evidence. |
| Course pass | You can complete the practical task on demo, explain the decision rules, show evidence, and name the conditions where the idea must not be used. |
| Strong pass | You can teach the concept to someone else, find edge cases, document a rejected example, and improve the template without weakening risk controls. |
Advanced homework
- Create five deliberately bad trade requests and document exactly where each one should be rejected.
- Build a state diagram for order request, check, send, fill, modification, close, reject, and recovery paths.
- Run the same EA on a demo hedging account and a demo netting account, then document lifecycle differences.
Practical drill
Do this lesson as a controlled exercise, not as a reason to trade live. Open a demo account or notebook, write the lesson title, and record what you changed, clicked, calculated, or checked. If the lesson includes code, compile it only in a demo environment and keep the original version unchanged so you can compare edits safely.
- Write a one-paragraph explanation of execution quality monitor: slippage, spread, rejects, and fills in your own words.
- Take one screenshot or note that proves you completed the platform, maths, research, or code task.
- Record one risk rule that would stop you from using this idea with real money.
- If anything feels unclear, repeat the lesson before moving to the next module.
How scammers misuse this topic
Scammers often take real concepts and wrap them in urgency. They may use platform jargon, bot screenshots, copied profit charts, or official-sounding language to make a paid offer feel safe. A real concept is not the same as a safe offer. Before paying anyone, ask whether you can verify the provider, reproduce the calculation, test the claim on demo, understand the risk, and walk away without pressure.
Checkpoint before continuing
- You log requested and filled prices for tested orders.
- You can explain when execution conditions invalidate a strategy result.
- Your review separates signal quality from execution quality.
Official references
These lessons are written as free education. When platform features or rules matter, verify against the official source before using real money.
Risk note: leveraged forex and contracts for difference can lose money quickly. EarnSouthAfrica is an educational publisher, not a broker, adviser, signal provider, or money manager.
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