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MT5 records every deal with requested price (for pending orders and stops) and executed price. Exporting this into a spreadsheet lets you measure slippage properly instead of relying on impressions.

Steps:

1. In MT5, open History, right-click, select the period, then "Report" or save as HTML/XLSX depending on version.
2. Import into a spreadsheet.
3. For each stop and limit order, calculate: slippage = executed price - requested price (adjusted for direction).
4. For market orders, compare execution price with the price on the chart at click time (harder, as the requested price isn't always stored).

Useful columns to add:
- Session (Asia, London, NY).
- Order type.
- Pair.
- Minutes since last major news.

Pivot tables then show average slippage by session, order type and pair. Over a few hundred trades, patterns become clear: perhaps stop orders on GBPJPY at 08:00 slip 0.8 pips on average while limits fill at the requested price.

Has anyone built a reusable template for this? It would be a useful community resource.

The default in most testers is zero slippage, which already tells you the results are a best case. The harder question is what number to replace it with, and the honest answer is that no single number is right.

Is slippage a flat amount per trade? That treats a market order on a quiet Tuesday afternoon the same as one fired during a payroll release. It also ignores direction. Slippage on stop orders tends to be worse than on limit orders, because a stop turns into a market order exactly when price is moving away. Limit orders can fill at the price or better, or simply not fill at all, which is a different kind of cost: missed trades rather than worse prices.

Maybe it should scale with volatility, so a bigger recent range means more slippage. That feels closer to reality, though it still needs a calibration source. The most credible source is the account's own history: compare the requested price on each live order with the actual fill, split by order type and by time of day, and look at the averages and the tails. The tails matter most. A strategy can survive an average of 0.3 pip and still get wrecked by a handful of 3 pip fills on stops.

Another angle is to ask how much slippage the strategy can afford before the expectancy hits zero. That breakeven number is often more informative than any estimate of actual slippage, because it shows how much margin of safety exists.

Does anyone track fill versus requested price long enough to build a slippage profile by session?