Slippage: Backtest Versus Reality
A backtest is almost always more optimistic than reality, and slippage is one of the main reasons. On historical data an order fills at an ideal price; in life it fills at whatever price exists.
Slippage: why the asymmetry is unavoidable
Slippage is distributed unevenly between order types, and this is the crucial point. A limit entry either fills at your price or does not fill at all — favourable slippage barely exists there. A stop-loss, by contrast, triggers as a market order precisely when price is moving fast against you, in the worst possible conditions. The result is that good outcomes arrive at the planned price and bad ones at a worse price.
How to model it
The simplest workable approach is to subtract a fixed number of pips from every trade on entry and exit, taking the figure from your own statistics or with a margin. A more honest model makes slippage conditional: larger around releases and in thin hours, smaller when the market is active. A perfect model is impossible without data on real fills, so the aim here is not accuracy but understating the result rather than overstating it.
The sensitivity test
More useful than any single number is checking how the result changes across cost assumptions. Run the system with zero slippage, with a realistic figure, and with double that. If it stays profitable at the doubled figure it has a margin of safety. If profit disappears at the realistic one, you were testing execution quality rather than a strategy.
Where the error costs most
The shorter the average trade, the more destructive the effect. A system targeting tens of pips survives a couple of pips of slippage; one targeting a few pips does not. For intraday and high-frequency approaches, modelling costs matters more than choosing the entry rules themselves — costs determine the sign of the result, not merely its size.
This material is educational and is not individual investment advice. Backtested results do not guarantee similar results in the future. Trading forex carries the risk of losing capital.
Frequently asked questions
Why does a backtest show better results than live trading?
One of the main reasons is idealised execution on historical data. In reality stops fill with slippage exactly during fast moves, and limit entries sometimes do not fill at all.
How do I build slippage into a backtest?
The simplest way is to subtract a fixed number of pips on entry and exit, taken with a margin. Precision matters less than the direction of the error: better to understate the result than overstate it.
How do I know whether a strategy is robust to costs?
Run it with zero, realistic and doubled costs. If profit disappears at the realistic level, the system depends on execution quality rather than on its own rules.
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