What Is a Worked Example of Weekend Risk?

Direct answer

A worked example of weekend risk is a numerical scenario that translates the idea of “unexpected price movement during the weekend gap” into an account-level impact estimate. Because the actual gap and trading conditions are unknown, the example must state assumptions (for prices, position size, and costs) and show how changes in those assumptions change the estimate.

Mechanism or definition

Weekend risk in forex is usually discussed as a risk of price movement between the last trading price before the weekend and the first executable prices after reopening. This risk is not limited to “news”—it also includes liquidity changes, market order-book conditions, and differences in how execution occurs when markets reopen.

A useful worked example focuses on the mechanics you can verify independently:

• You choose an illustrative starting price and an end-of-weekend reopening price (assumptions).
• You define the position size in units (assumption) and the pip value conversion (assumption based on the instrument).
• You compute the profit or loss from the assumed price difference.
• You optionally include typical costs conceptually (spread/commission/slippage) as assumed add-ons, then show sensitivity.

Stable mechanics (the part you can calculate the same way regardless of broker or platform):

• P/L depends on the price difference between two levels.
• Account impact depends on position size and pip value.

Variable conditions (cannot be known in advance):

• Whether the reopening price gaps and by how much.
• Execution quality (fills), effective spreads, and any additional fees.

Evidence or example (transparent numerical scenario)

Assume a simplified EUR/USD example with these stated assumptions:

1. Current price before weekend close: 1.1000 (assumption).
2. Hypothetical reopening price after the weekend: 1.1060 (assumption).
3. Price difference: 0.0060.
4. Pip size for EUR/USD: 0.0001.
5. Pip movement: 0.0060 / 0.0001 = 60 pips.
6. Position size: 10,000 EUR (assumption; a common “standard lot” in many educational examples is 100,000, but we keep it explicit by using units).
7. Pip value: assume $1 per pip for this position size and currency conversion (assumption; a reader should adjust if their account currency differs).
8. Direction: you are long (benefits if price rises).
9. Weekend costs: ignore costs for the first pass (assumption), then show an optional cost sensitivity.

Calculation (first pass):

• Estimated gain = 60 pips × $1/pip = +$60.

Now show sensitivity with a different assumed reopening price:

• If reopening were 1.0970 instead, the price change would be -30 pips.
• Estimated P/L would be -30 pips × $1/pip = -$30.

Optional cost sensitivity (still assumptions):

• Suppose you model “effective trading friction” during reopen/quote changes as an additional $10 total cost (assumption).
• Then the long scenario becomes +$60 − $10 = +$50.
• The loss scenario becomes -$30 − $10 = -$40.

What this demonstrates:

• The calculation is straightforward once assumptions are fixed.
• The uncertainty is concentrated in the unknown reopening price and the unknown effective costs.

Limitations and risks (material failure modes)

1. Unknown gap size: The most material limitation is that the reopening price difference can be larger or smaller than your assumed level, making the estimate potentially far off.
2. Execution and pricing differences: Even if the “market price” jumps, your actual fill price may differ due to liquidity and order handling, so the realized result may not match your assumed two-level calculation.
3. Pip value and account currency: The pip-to-account-currency conversion depends on instrument details and account currency. If those assumptions are wrong, the computed P/L in money terms can be incorrect.
4. Costs are not constant: Spreads, commissions, and slippage can change around reopen. Treating costs as zero (or a fixed add-on) can understate or overstate impact.

Historical relationships do not establish future results. A scenario that “looked plausible last time” cannot justify expecting the same pattern again.

Verification and next question

To independently verify a worked example like this, check that every assumption is explicitly stated and then redo the math with your own hypothetical levels and your own unit-to-pip value conversion.

Common next question: how would the account risk estimate change under a different instrument, different account currency, or a different position size? These variations keep the mechanics the same but change the sensitivity to a hypothetical weekend gap.