Direct and indirect costs that shape slippage assumptions
Slippage assumptions are estimates of how much worse (or occasionally better) the actual execution price can be compared with a reference price used in a model. In forex-related planning, a “reference” might be a quoted price, a mid price, or an intended entry/exit level. The key idea is that slippage is not only a price difference; it is often the result of cost components and timing mismatches.
Direct costs (visible in pricing terms)
Direct costs are those that typically appear explicitly in the trading record or the pricing inputs. Common examples are:
- Spread-related effects: If your model assumes you will execute at one side of a quote (or at mid) but the market moves between decision time and fill time, the realized price can differ. Even without extra fees, the spread and how you reference it can change the implied slippage.
- Commissions or execution fees: If you include commissions in a backtest or calculation, but exclude them in another version, your “assumed slippage” will effectively compensate for missing costs.
- Financing costs (carry) and swap adjustments: If positions are held, financing can change the overall realized outcome. While not always labeled “slippage,” it can still be folded into the assumptions behind net trade outcomes.
Indirect costs (often hidden in execution mechanics)
Indirect costs arise from how orders interact with the market and the platform’s execution pipeline. Examples include:
- Latency and timing mismatch: The time between when an order is generated, when it reaches the execution venue, and when it is filled can cause the fill price to reflect new market conditions. This changes slippage even if spreads and commissions are unchanged.
- Liquidity impact: If the market depth available at the time of execution is thinner than assumed, larger orders (or orders during sudden volatility) may move the effective execution price away from the reference.
- Partial fills and re-quoting: If an order is filled in parts or subject to changing execution conditions, the average fill can deviate from the single-price assumption often used in simplified models.
- Order type and execution rules: Assumptions can fail if the model assumes immediate execution at the reference, while real execution uses constraints such as minimum fill conditions, re-pricing, or time-based handling.
How the costs “work” inside the assumption
To understand how costs affect slippage assumptions, separate the calculation into two layers:
- Price-reference layer: What price does your model start from (mid, bid/ask, last, or a specific quote time)? A mismatch between the reference used in the assumption and what is actually achievable at execution time creates apparent slippage.
- Fill-process layer: Which costs and execution effects are included in the model’s fill price (fees, commissions, spread interpretation, and timing)? If fees are handled elsewhere in your net calculation, you should not double-count them inside slippage.
A practical way to keep assumptions coherent is to write them as a consistent chain of inputs: reference price definition → expected execution moment (timestamp basis) → included cost components → how to translate them into an estimated fill price.
A verification approach you can do independently
Without relying on live data, you can still verify whether your slippage assumptions match reality by using the records you already have (for example, completed trade logs from an execution system or platform reports).
- Use consistent reference definitions: For each executed trade, compute the reference price using the same rule your model used (e. g. , mid vs bid/ask). If you used mid in the assumption, also derive mid at the same reference timestamp rule. 2. Compare forecast vs realized fill: For each trade, measure the difference between the realized execution price and your model’s reference price. Then compare the distribution of these differences with your assumption (for instance, whether your assumption consistently overstates or understates typical deviations). 3. Account for cost components separately: Record explicit costs (fees, financing adjustments if applicable) and keep them distinct from pure price deviation. This prevents confusing “net outcome differences” with “execution slippage. ”
- Check sensitivity to variable factors: Repeat your calculation using slightly different reasonable inputs for spread interpretation, execution timing, and order size effects.