Pulling order history to measure slippage honestly

[Amanhasnoname]

Most traders feel they know their slippage, but few have measured it. The data is available in the platform's history.

Export the order history, including the requested price for pending orders, and the fill price. For market orders, record the quote at the time of sending by using a script or screenshot, since the platform does not always store it.

With a few hundred trades, compute the average and the distribution of the difference between expected and actual prices, separately for entries and exits, and for winners and losers.

The numbers usually surprise. Average slippage may be small, but the tail, the worst ten percent, can hold most of the cost.

Break it down by time of day, pair, and size. Patterns appear: worse at the NY open, better in London, higher on crosses.

With that information, filters and expectations can be adjusted to match reality. It also becomes a concrete basis for conversations with the broker.

What does the slippage distribution look like on your account, and where is the tail?