Direct answer
A worked example of “EA definition” is a step-by-step, numeric scenario that shows what an Expert Advisor (EA) definition contains: the fixed decision rules (what it does) and the assumed inputs or environment (what may change). The purpose is to make the EA definition explainable and independently checkable by stating every assumption.
Mechanism or definition
An EA (Expert Advisor) is automated trading software. An “EA definition” in practice means writing down two things separately:
- Fixed mechanics (stable within your definition)
- Entry/exit logic: the exact conditions that must be true.
- Order rules: type (market/limit), trigger timing, and any constraints.
- Money rules: how position size is determined (for example, a fixed lot size or a formula).
- Variable conditions (not guaranteed)
- Market prices and liquidity at execution time.
- Costs: spread, commissions, swap/overnight charges.
- Execution quality: latency, slippage, and order rejections.
- Provider or platform settings and limits.
A worked example then uses a small scenario to show how the fixed mechanics operate under stated assumptions.
Evidence or example (worked scenario)
Example EA definition (simplified):
- Fixed rule A (entry): Open 1 position when Price at/above a trigger level.
- Fixed rule B (exit): Close when Price reaches trigger+Δ.
- Fixed rule C (size): Use a fixed size “1 unit” and do not change it.
Assumptions for this worked example (all explicitly stated):
- Trigger level: 100.0
- Target distance Δ: 1.0
- Costs: commission+spread impact total = 0.10 (combined) per completed trade
- Slippage: zero (we assume execution equals the modeled price)
- No rollover/overnight charges
- Only one trade happens in the scenario
Scenario timeline:
- At time T1, the market price reaches 100.0 → rule A is satisfied.
- The EA opens at an assumed effective entry price of 100.0.
- At time T2, the market price reaches 101.0 → rule B is satisfied, and the EA closes.
Gross price movement:
- Exit price 101.0 minus entry price 100.0 = +1.0
Net result after costs (given assumption that costs total 0.10):
- Net = +1.0 − 0.10 = +0.90 (in “price movement units” for the chosen 1 unit size)
What this illustrates about “EA definition”:
- The +1.0 comes from the stable mechanics and the chosen price path in the scenario.
- The −0.10 comes from the variable cost assumption you included.
- If you change the assumptions (for example, add slippage or a larger spread), the net result changes even though the EA definition rules remain the same.
Limitations and risks
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Market and execution variability Even with the same EA definition, real outcomes can differ because execution quality may not match modeled prices. Slippage can reduce results; rejected orders can prevent the exit rule from running.
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Costs and timing sensitivity Backtests often understate real costs or timing differences. Spread changes, commissions, and order-fill timing affect net results.
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Scenario mismatch A single worked example is not evidence of future performance. Historical relationships do not establish future results, and a path that hits +1.0 in the example may not occur.
Verification or next question
To independently verify an “EA definition” worked example, check that:
- Every rule is unambiguous (what exact conditions trigger entry and exit).
- Every calculation assumption is stated (effective entry/exit prices, and what costs are included).
- Variable factors are separated from fixed mechanics.
A useful next step is to rewrite the same example with one changed assumption (for example, introduce slippage or increase cost) and show how the net outcome changes while keeping the EA definition rules constant.