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Lesson 67MT5 systems engineeringAdvanced195 min

OnTester custom optimization criteria and robust selection

Go beyond net profit by designing custom optimization criteria that penalize fragile, overfit, high-drawdown, and low-sample systems.

Lesson outcomes

  • Understand how custom tester criteria can guide optimization.
  • Design objective functions that reward robustness instead of marketing-friendly profit.
  • Build a result-selection process that includes rejection thresholds.

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.

The Strategy Tester can optimize parameters, but the target metric matters. If you optimize only for net profit, the machine may find a fragile curve-fit that looks amazing and collapses under costs or new data.

OnTester lets advanced users calculate a custom criterion for optimization. This lesson uses it to teach humility: optimize for survival, quality, and robustness, then reject most results.

What you should be able to do after this lesson

  • Understand how custom tester criteria can guide optimization.
  • Design objective functions that reward robustness instead of marketing-friendly profit.
  • Build a result-selection process that includes rejection thresholds.

Criterion design

MetricWhy include it
Net profitUseful but dangerous alone because it ignores path and fragility.
Maximum drawdownPenalizes results that require emotional or financial survival beyond the learner's limits.
Trade countBlocks tiny-sample miracles that are not enough evidence.
Stability scoreRewards parameter areas that remain acceptable across nearby settings.

Bad optimization incentives

  • Maximizing profit while ignoring drawdown, lot escalation, and exposure concentration.
  • Rewarding a high win rate when average loss is much larger than average win.
  • Selecting the single best parameter row instead of a stable neighbourhood.
  • Treating the optimization winner as live-ready without forward testing.

Selection memo

Every optimization run should end with a memo: objective function, date range, costs, forward window, rejection rules, top candidates, stable ranges, and why most rows were not selected. The memo is more important than the winning row.

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 elementWhat you must produce
Primary artifactEA systems engineering dossier
Lesson focusOnTester custom optimization criteria and robust selection
Working environmentDemo account, notebook, exported platform data, or local code sandbox. Never live funds for first practice.
Completion standardYou 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 ontester custom optimization criteria and robust selection 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.

FieldStandard
Preflight areaAccount mode, symbol specification, margin, stops/freeze level, spread, session, and permission state.
Event handlerOnTick, OnTimer, OnTradeTransaction, OnBookEvent, OnCalculate, or OnTester responsibility.
Safety gateThe exact condition that blocks duplicated, oversized, stale, unfillable, or undocumented trades.
EvidenceJournal/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 ontester custom optimization criteria and robust selection 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

LevelWhat it looks like
Not readyYou can repeat the vocabulary but cannot complete the demo task, calculate the risk, explain the failure mode, or show evidence.
Course passYou 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 passYou 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 ontester custom optimization criteria and robust selection 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 can explain why profit alone is a weak optimization target.
  • Your criterion includes penalties or rejection rules for fragile results.
  • You select robust parameter regions, not a single lucky row.

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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