Slippage by hour of the day as a standing statistic
Posted: Sat Oct 31, 2026 6:37 am
Overall slippage averages hide huge differences between hours. Fills during the London open may be excellent, while those at rollover are terrible, and the average lands somewhere meaningless.
Maintaining a running table of slippage by hour, by pair, and by order type provides a real-time guide. Each trade adds a row, and after a few hundred trades, the pattern is clear.
The table supports decisions. Hours with consistently poor slippage can be avoided or traded with wider tolerances. Pairs with unusual fill quality can be dropped or approached differently.
It also allows testing changes. Switching VPS, changing the account type, or adjusting the deviation setting shows up in the numbers within a few weeks.
The effort is small if the log is automated. Many platforms export history with prices and times, and a simple script or spreadsheet processes the rest.
After a month, the hours worth avoiding usually stand out so clearly that nobody needs to argue about them.
Is slippage tracked by hour, and which window turned out to be the most expensive?
Maintaining a running table of slippage by hour, by pair, and by order type provides a real-time guide. Each trade adds a row, and after a few hundred trades, the pattern is clear.
The table supports decisions. Hours with consistently poor slippage can be avoided or traded with wider tolerances. Pairs with unusual fill quality can be dropped or approached differently.
It also allows testing changes. Switching VPS, changing the account type, or adjusting the deviation setting shows up in the numbers within a few weeks.
The effort is small if the log is automated. Many platforms export history with prices and times, and a simple script or spreadsheet processes the rest.
After a month, the hours worth avoiding usually stand out so clearly that nobody needs to argue about them.
Is slippage tracked by hour, and which window turned out to be the most expensive?