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Brokers love to say that slippage works both ways. Sometimes you get a better price than requested, sometimes worse, and over time it balances. That's what the theory says.

In practice, a lot of traders who keep a simple ledger find a lopsided picture: lots of small negative fills, and positive ones that are rarer and smaller. The positives are sometimes just not passed on, because the broker keeps the improvement.

The test takes ten minutes to set up. Export the trade history, and for each market order compute the difference between the price on the screen at click time and the actual fill. This requires either screen recordings or an EA that logs the quote at the time of the order, but a basic script can do it.

After a few hundred trades, sort by size. If the average negative slippage is 0.3 pips and the average positive is 0.05, with equal counts, the cost is real.

It also matters by time of day. Symmetry may hold in quiet London hours and break at news or rollover.

Anyone who has actually measured this: what did the ratio of good fills to bad fills look like?

I measured it on about four hundred market orders with a small EA that wrote the bid and ask to a file at the moment it sent each order. Roughly half the fills were exactly at the requested price, and of the rest, the negative ones outnumbered the positive ones by close to three to one. The positive fills were also smaller, usually a tenth or two, while the bad ones were often half a pip or more.

The time of day point matched my data. In the middle of the London morning the split was much closer to even, and most of the lopsidedness came from the first minutes after data releases and from a handful of trades near the daily close.

The useful thing for me was putting a number on it. Once I knew my average slippage was about 0.15 pips per trade, I added it to my cost assumptions, and a couple of setups that looked profitable on paper turned out to be roughly flat. I stopped trading those.