What “slippage around news” means
Slippage around news refers to the gap between a price you expected to get (often based on a quote or a planned entry) and the price you actually receive when your order executes. The “around news” part matters because fast information releases can increase trading activity and reduce how stable quotes are.
A key point is that slippage is not a single guaranteed effect. It is an outcome of execution conditions, not a prediction. Your expected price may come from a last traded price, a bid/ask quote, or an average fill you observed earlier; those can differ even without news.
How the most common mistakes happen
1) Confusing slippage with market volatility
A common misunderstanding is treating slippage as identical to volatility. Volatility is how much prices can move; slippage is the difference between the expected and filled price for a specific order. You can experience low volatility but still see slippage if execution is delayed or liquidity is thin.
2) Using an “expected price” that was never executable
Another frequent mistake is computing “slippage” from a quote that the order could not realistically achieve at the moment of execution. For example, if your expected price was a stale quote, or if your order type could fill at different prices than the displayed mid-price, the comparison is flawed.
Neutral check: Define what “expected price” means in your calculation (bid, ask, last trade, or a targeted limit). Otherwise you cannot reliably explain why results differ.
3) Assuming past news behavior will repeat
News releases can change how liquidity and spreads behave, but the specific reaction varies by context: market positioning, the direction of the surprise, and how many participants act simultaneously. Treating historical averages as if they guarantee similar future fills is a reasoning error.
4) Ignoring costs and execution frictions
Many evaluations focus only on price difference and overlook related costs. Spreads, commissions/fees, and any execution constraints can affect effective results. If you compare gross price change without including these factors, you may wrongly attribute the entire discrepancy to slippage.
5) Mixing measurement windows (timestamps problem)
“Around news” is often measured inconsistently. One person compares fills to the time the news hits the market; another compares to a later moment when the order finally executes. Even a small timing mismatch can create an apparent “slippage” effect that is mostly a measurement artifact.
A simple, neutral example (with stated assumptions)
Assume:
- Your “expected price” is the quote you saw at order submission time.
- You place an order that executes immediately when liquidity is available.
- You record the first fill price when the execution occurs.
If the quote at submission was 1.1000 but your first fill was 1.0975, slippage (by this definition) is 0.0025. Now suppose the spread at submission was wide and the order could not trade at the mid. A different definition of “expected price” (using the ask for a buy, or bid for a sell) may change the slippage number without changing the market.
Material limitations and failure modes
- Execution variability: Two identical-looking orders can fill differently depending on queueing, partial fills, and liquidity at the exact execution moment.
- Provider or venue effects: Execution quality can differ based on how orders are routed and matched; this can change the observed slippage pattern.
- Biased comparison: If you select only the trades with large differences, or if you use inconsistent expected-price definitions, your conclusion becomes unreliable.
- Non-causality: Large slippage on a news day does not automatically prove the news caused it; other simultaneous events can contribute.
Verification: how to check your claims independently
- Log your inputs: Record the expected-price definition, order type, and the exact times of submission and fill.
- Use consistent comparisons: Apply the same slippage formula to all relevant trades, not only outliers.
- Separate effects: Compare price moves (market context) versus execution outcomes (fill quality) using the same time window.
- State assumptions: If your “expected price” comes from bid/ask/last/mid, note it clearly; otherwise readers cannot verify your arithmetic.
- Assess limitations: Confirm whether your analysis is affected by stale quotes, partial fills, or missing fee/spread components.