Slippage is rarely symmetrical, so check the sign
Posted: Thu Oct 29, 2026 3:52 am
Most traders talk about slippage as one number, like 0.3 pips average. That single figure hides the part that matters, which is the sign.
Positive slippage means the fill came in better than requested. Negative means worse. On a clean feed with deep liquidity, the two tend to roughly offset over a large sample. On a feed where positive slippage is capped, rejected, or repriced back to the requested level, the average drifts negative with no obvious cause.
The check takes ten minutes in a spreadsheet. Pull every fill from the last month, subtract requested from filled, flip the sign for sells, and plot the distribution. A healthy distribution has two tails. A lopsided one has a long tail on the bad side and a stump on the good side.
That lopsidedness is worth far more than the average figure, because it says something about how the order is being handled rather than just how volatile the market was.
A useful extension is to chart slippage against time of day. Quiet hours often show tiny, balanced slippage, while the minutes around data releases show wide, lopsided distributions. Seeing both on one chart makes it clear whether the problem is general or concentrated in a few windows that can simply be avoided.
What does the slippage distribution look like on your own fills, and is it two-tailed or lopsided?
Positive slippage means the fill came in better than requested. Negative means worse. On a clean feed with deep liquidity, the two tend to roughly offset over a large sample. On a feed where positive slippage is capped, rejected, or repriced back to the requested level, the average drifts negative with no obvious cause.
The check takes ten minutes in a spreadsheet. Pull every fill from the last month, subtract requested from filled, flip the sign for sells, and plot the distribution. A healthy distribution has two tails. A lopsided one has a long tail on the bad side and a stump on the good side.
That lopsidedness is worth far more than the average figure, because it says something about how the order is being handled rather than just how volatile the market was.
A useful extension is to chart slippage against time of day. Quiet hours often show tiny, balanced slippage, while the minutes around data releases show wide, lopsided distributions. Seeing both on one chart makes it clear whether the problem is general or concentrated in a few windows that can simply be avoided.
What does the slippage distribution look like on your own fills, and is it two-tailed or lopsided?