Trading journal columns: which fields to record

A trading journal is only as good as the questions its columns let you answer later. Here is a field list that stays small enough to fill on every trade and still supports every split worth running.

Every column has to answer a future question

Before adding a field, name the question it will answer. 'Entry time' answers 'which session do I trade best'. 'Model' answers 'which of my ideas actually has an edge'. 'Followed plan' answers 'are my losses the strategy or me'. If you cannot name the question, or you have never once filtered by the field, it is costing you time on every trade and giving nothing back. This test matters because the main failure of trading journals is not missing data but abandoned data: a sheet with forty columns gets filled carefully for ten days and then not at all. A short list filled on every single trade produces statistics you can trust. So treat the list below as a menu with a clear purpose for each item, and cut anything you will not use.

The basics: when, what, which way, which account

Start with date and time of entry and exit, the instrument, direction, and the account. Time looks trivial but it is the raw material for two important splits: session, because many traders have one session that pays and one that quietly bleeds, and holding time, which shows whether your winners and losers behave differently. Record time in one fixed time zone, otherwise daylight saving changes will shift trades between sessions twice a year. The account field matters as soon as you run more than one. A prop evaluation, a funded account and a personal account have different rules, different drawdown limits and often different behaviour from the same trader. If they live in one undivided list, a breach on one account and a good month on another blur into a single meaningless average.

Risk and result: price, size, money and R

Record entry, stop, target and position size, then derive three numbers: risk in money, net P/L in money after commission and swap, and the result in R, which is net P/L divided by the risk you planned. A worked example: you risk $100 and close for $250 net, so the trade is +2.5R. Another trade risks $100 and loses $100, so it is -1R. Keep both planned and realised reward to risk. If you plan 3:1 trades but your realised average winner is 1.4R, you are cutting winners early, and no amount of staring at the money column would have shown it. R is the field that lets you compare trades across different account sizes and different risk levels, which makes it the single most useful number in the journal.

Context: model, session, timeframe

These are the columns you will group by. Model is the name of the repeatable idea behind the trade, such as 'Asia range sweep' or 'trend pullback to the 20 EMA'. Session is London, New York, Asia or your own split. Timeframe is the chart you made the decision on. Some traders add a market condition tag such as trending or ranging, which is useful only if the definition is written down and applied the same way each time. The key is a fixed vocabulary: choose the names once and pick from the list rather than typing freely. Inconsistent spelling is the quietest way to ruin these columns, because a model logged under two names shows up as two half-sized samples, each too small to judge.

Execution: did you follow the plan

This is the column traders leave out and later wish they had. Make it a simple yes or no: did this trade follow my written rules. Then add mistake tags from a short fixed list, for example early entry, moved stop, oversized, chased, no stop, and closed early. Keep the list to six or eight tags; if every trade gets four tags, none of them mean anything. The value shows up when you sum results by tag. As an illustration, if ten trades tagged 'moved stop' total -6R while the rest of the month is +4R, you have found a specific behaviour that turned a positive month negative, and it is a behaviour you can change by next week. An emotion field can sit here too, but it is only useful if you record it consistently.

Evidence: screenshots and a short note

Attach a screenshot at entry, showing what you saw when you decided, and one after exit, showing what happened. Mark the entry, stop and target on the chart before you capture it. Then write a note of one or two sentences: why you entered and, after the close, what you would do differently. Short notes get written; long ones get skipped. Screenshots matter more than they seem, because in a weekly review a picture of the chart at the moment of decision is the only honest way to judge whether the entry matched the model, without hindsight from the rest of the move. In Haunted, screenshots and notes sit on the trade itself next to the outcome, R:R, risk, session, model and tags, so the review happens in one place.

Fields that look useful but usually are not

Some columns feel professional and rarely earn their place. Indicator readings at entry are usually visible on the screenshot already. A confidence score from one to ten tends to drift toward seven, unless every number has a written definition. Long free-text fields for market commentary get filled for a week and then copied and pasted. Separate columns for every partial close turn a simple log into accounting; recording the net result and the average exit is usually enough. Fields copied from someone else's template are the most common offender, because they answer that trader's questions, not yours. Start with the minimum, run it for a month, and only add a column when a review raises a question your current fields cannot answer.

What is the minimum set of fields for a trading journal?

Date and time, instrument, direction, account, risk in money, net P/L, result in R, model, session, followed plan yes or no, and an entry screenshot. That is enough to calculate expectancy and split results by model and session, which covers most of what a review needs.

Should I record commissions and swaps?

Yes, and the simplest way is to record net P/L after all costs. For short-term traders, commission can turn a model that looks profitable on gross numbers into one that is flat or negative. Calculating R from the net figure keeps the statistics honest.

Is it better to track results in money or in R?

Track both, but analyse in R. Money tells you what happened to the account. R tells you how the strategy performed independently of position size, so it lets you compare a month at 0.5% risk with a month at 1% risk, or a prop account with a personal one.

How many tags should I use?

Fewer than you think. Six to eight mistake tags and a short list of models are usually enough. Each tag should be defined in one sentence so you apply it the same way every time. A tag used on almost every trade, or almost never, should be merged or removed.