Direct answer
A worked example of risk rules is a fully numerical scenario that shows how a trader turns an agreed maximum loss per trade (the loss tolerance) into a concrete position size, step by step. The “worked” part means every input value and unit is stated, and the calculations can be checked independently.
Mechanism or definition
Risk rules typically separate two ideas:
- Stable planning mechanics: the rule you choose for the math (for example, “risk 1% of account equity per trade”).
- Variable execution conditions: what happens in live markets, such as spreads, slippage, and whether the exit price is actually reached.
A common risk rule workflow looks like this:
- Choose a risk amount you are willing to lose if the trade goes the wrong way.
- Choose a price movement distance that you treat as your “stop distance” (how far the entry is from the assumed exit level).
- Convert the risk amount into position size using the relationship between price movement and value at risk.
Because terminology varies across platforms, it helps to define units explicitly in your example: account currency, trade size units, and whether your calculations assume exact fill prices.
Worked evidence via a scenario example
Below is one worked example using simplified, checkable arithmetic. No real-time prices are assumed.
Assumptions (state them up front)
- Account equity: €10,000.
- Risk rule: risk 1% of equity per trade.
- Risk distance: 1.00 “price unit” between entry and the assumed exit level.
- Value per “price unit” for the chosen instrument at the selected size: €50 per price unit.
- Costs (spread/fees) and slippage: ignored for the calculation example.
Step 1: compute the maximum loss in euros
Risk amount = €10,000 × 1% = €100.
Step 2: translate risk amount into position size
If the instrument produces €50 loss per 1.00 price unit at a given size, then a 1.00 unit adverse move would cost €50 for that size. To reach €100 at the same 1.00 distance:
- Required scaling factor = €100 / €50 = 2.
- Position size used in the example = 2× the base size that yields €50 per price unit.
What you can verify
Someone else can verify the math by checking:
- 1% of €10,000 equals €100.
- The risk distance used is exactly 1.00.
- The value-per-distance assumption (€50 per price unit for the base size) matches the scenario.
Limitations and risks
Even when the worked example is correct, real outcomes can differ because the example depends on assumptions that may not hold:
- Execution risk: if fills occur at worse prices than assumed, realized loss can exceed the planned €100.
- Costs risk: spreads and commissions can increase the effective loss, even if the stop distance is unchanged.
- Distance model risk: treating a “stop distance” as fixed ignores that markets can gap or move quickly.
- Model mismatch: value-per-price-unit relationships can change with instrument specifications, contract definitions, or account settings.
These failure modes are why worked examples should also include what is not modeled (like slippage and fees) so you understand the boundary of the calculation.
Verification or next question
To independently verify a risk-rules worked example, check whether it:
- states every assumption (account size, risk percentage, stop distance, and value-per-distance),
- keeps units consistent (currency and price units),
- clearly separates planning math from execution uncertainty.
A useful next question is: which parts of the calculation are you able to measure or confirm on your platform (especially cost and value-at-risk mechanics), and which parts are only assumptions?