A post-mortem framework for a very bad day

[Amanhasnoname]

Every scalper has a bad day, and the way it is analyzed determines whether it teaches anything. A structured post-mortem avoids both denial and self-flagellation.

Begin with facts. Gather the trade log, the execution data, the market conditions, and the timeline. Compare the day's statistics with normal: number of trades, average size, spread, slippage, and time between trades.

Classify the cause. Was it market conditions, such as a news event or a regime change? Execution, such as slippage or outages? Strategy, meaning the edge was absent or decayed? Or behavior, such as rule violations and emotional decisions?

Often several causes combine. Rank them by contribution to the loss.

Determine whether the day falls within the expected variance of the system. A bad day that fits the distribution requires no changes, only acceptance.

End with specific actions: a rule to add, a check to automate, a parameter to review. Limit to one or two changes.

Write it down. The record builds a library of lessons.

What categories organize a post-mortem, and which cause appears most often?