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A slippage audit in one spreadsheet

Anyone can audit execution quality without special software. The data needed: for each trade, the requested price, the filled price, the direction, the time, and the pair.

Compute slippage as filled minus requested, flipped in sign for sells so that positive always means worse for the trader. Convert to pips.

Add columns for the hour, the weekday, and whether the trade was an entry, a stop, or a target. A pivot table then shows the average and maximum slippage for each category.

Fifty to a hundred trades produce a rough picture. Three hundred or more give something solid.

The result guides decisions: which hours to avoid, which order types to prefer, which pairs cost more than they look. It also gives a baseline for judging a broker.

An hour of work every quarter keeps the numbers current and turns vague suspicion into a table.

First slippage audit done? Where did the costs turn out to concentrate?

I did my first one of these about eight months ago on around 220 trades, and the result surprised me. Entries were fine, almost all within a tenth of a pip. Nearly all the damage was on stop exits, which averaged close to half a pip worse than requested, and the worst fills sat within a couple of minutes of the US data releases I thought I was already avoiding.

The hour column was the most useful thing you mention. Once I pivoted by hour, the first fifteen minutes after the London open stood out on its own, so I now wait for that to settle before trading. It cost me a few setups, but the average exit improved noticeably over the next couple of months.

One small tip from doing it by hand: log the requested price at the moment you click, not from the chart afterwards. My first attempt used chart prices and it made the slippage look better than it really was. Most platforms keep the requested price in the order history if you dig for it.