What is price slippage and how do we model it?

Question

AcadiFi · Accepted Answer

Slippage is the difference between expected execution price (often the mid at decision time) and actual realized price. It comprises: (1) spread cost — crossing half the bid-ask, (2) market impact — permanent and temporary price moves from our order, (3) timing cost — price drift during execution, (4) opportunity cost — unfilled portions.

A simple linear slippage model: slippage_bps = a + b*(Q/ADV) + c*volatility + d*(1/liquidity_score) + epsilon. Coefficients calibrated from historical execution data.

Example: Broadmoor Industrial Partners executes a $5M buy order in a stock with ADV=$25M, daily vol 1.8%. Using calibrated model a=2, b=35, c=150, d=12, liquidity_score=0.85:
slippage = 2 + 35*(5/25) + 150*0.018 + 12/0.85 = 2 + 7 + 2.7 + 14.12 = 25.82 bps.
On $5M, that's $12,910 in slippage cost.

Decomposition helps optimization: if spread is 5 bps, impact 15 bps, timing 4 bps, opportunity 2 bps, we know where to focus. Trading faster reduces timing risk but raises impact. Algo strategies (TWAP, VWAP, Implementation Shortfall, POV) trade off these differently.

```mermaid
flowchart LR
  A[Decision price] --> B[Spread cost]
  B --> C[Impact cost]
  C --> D[Timing drift]
  D --> E[Realized price]
  E --> F[Total slippage]
```

For FRM, slippage models feed both LVaR (expected cost component) and stressed-scenario liquidity analysis (tail cost under crisis).

What is price slippage and how do we model it?

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