Impact scaling — same order, different sizes
Impact grows with the square root of size, not size itself. This is why splitting a large order into smaller pieces over time (see the TWAP calculator) lowers your realized cost.
| Order size | Participation of ADV | Predicted slippage | Cost ($) |
|---|
Predicting a fill, not explaining one
This model estimates impact before you trade. Once you know your actual fill, use the slippage calculator to size the realized cost, or true trade cost to combine it with fees and funding.
The square-root law of market impact
Institutional execution desks don't guess at slippage — they model it. The standard approximation, used across equities and crypto trading desks, is: expected impact % = Y × daily volatility % × √(order size ÷ average daily volume). Y is an empirically calibrated constant, typically 0.3–1 depending on venue microstructure and order routing quality; this calculator defaults to 0.5.
The key insight is the square root, not the ratio itself. A $50,000 order against $2,000,000 of daily volume (2.5% participation) predicts roughly 0.6% impact. Double the order to $100,000 (5% participation) and impact rises to about 0.9% — a 1.41x increase (√2), not 2x. This sub-linear scaling is exactly why splitting large orders into smaller pieces over time reduces total realized cost.
Participation rate matters as much as the raw dollar amount. A $10,000 order against Bitcoin's ~$30B daily volume is 0.00003% of ADV — impact is negligible. The same $10,000 against a micro-cap doing $500,000/day is 2% of ADV — impact can run into the low single-digit percent.
Related: slippage calculator (known cost), TWAP execution (reduce impact via splitting), true trade cost (fees + slippage + funding combined).
Frequently asked questions
What is market impact vs slippage?
Slippage is measured after the fact — quoted vs executed price. Market impact predicts that same gap before you trade, from order size, volume and volatility.
What is the square-root law?
The standard institutional model: impact scales with the square root of participation rate (order size ÷ ADV), not linearly. Doubling size multiplies impact by about 1.41x, not 2x.
Why square root and not linear?
Order books have depth at multiple price levels and markets partially recover between fills. Decades of institutional execution research converge on the square-root form as the best simple approximation.
How do I calibrate the impact constant Y?
Default is 0.5. If you know a past trade's realized slippage %, back it out: Y = observed slippage % ÷ (volatility % × √participation). Enter that Y to calibrate future predictions to your own venue.
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