Direct answer
A worked example of scale in shows the arithmetic of adding to an existing forex position in multiple entries, so you can see how the average entry price changes. “Scale in” is not a guarantee of better results; it is a position-management method where the timing, size, execution quality, and costs determine outcomes.
Mechanism and definition
Scale in (in forex trading) generally means: you already have an open position, and you place additional orders later instead of entering the full size at once. The key quantities are:
- Initial position size: how much exposure you start with.
- Additional entries: further orders with specified sizes.
- Entry prices: the prices at which each portion is filled.
- Average entry price: the volume-weighted mean of fill prices.
To keep the example independent of live data, we assume fixed fill prices and fixed sizes.
Worked numerical example (with explicit assumptions)
Assume you are placing long exposure (buying) in a single currency pair. You make three entries.
Assumptions (state every input):
- The position is measured in equal “units of size” for simplicity (for example, equal lot fractions).
- You buy in three steps of sizes: 1, 1, and 2.
- Each entry fills at the following prices (these are hypothetical): 1.1000, 1.0950, 1.0900.
- Ignore fees, spreads, and slippage for the calculation of the average entry price.
Step 1: compute total size Total size = 1 + 1 + 2 = 4.
Step 2: compute volume-weighted average entry price Average entry price = (1×1.1000 + 1×1.0950 + 2×1.0900) / 4 = (1.1000 + 1.0950 + 2.1800) / 4 = 4.3750 / 4 = 1.09375.
Interpretation (what scale in changes):
- If later entries occur at lower prices (as assumed here), the average entry price decreases compared with only the first entry.
- That can make it easier for price to reach break-even on the position in price terms, because your blended cost basis is lower.
Important uncertainty note: In real execution, later fills might not occur at your expected levels. Spreads and slippage can also change the effective fill prices, so the average entry price may differ from the hypothetical arithmetic.
Limitations and risks (including failure modes)
- Costs can remove the average-price advantage. Even if the average entry price improves, each additional entry can increase the impact of spreads/fees and reduce realized net gains.
- Wrong-direction movement can increase risk. Scale in increases total exposure. If the market moves against you more than expected, losses can grow because you own more position size.
- Execution risk and partial fills. Orders may fill at different prices than planned, and additional entries might be partially filled, changing sizes and the computed average entry price.
- Path dependence. The result depends on the sequence of prices and fills. The same final price can lead to different outcomes if entries happened differently.
- Assumptions may not hold. A worked example uses hypothetical prices and simplified sizing. Historical relationships do not guarantee future behavior.
Verification and next question
To independently verify a scale-in calculation, reproduce the math with your own assumptions:
- Record the fill prices for each entry.
- Record the size of each entry.
- Compute the volume-weighted average entry price using (sum of size×price) ÷ (sum of size).
A useful next question is: which inputs in your plan are controllable (order sizes, execution timing, allowed slippage), and which are not (future market prices, spreads at execution time)?