Journal columns: why R next to dollars catches things dollars hide

[Fairman]

Journal columns: why R next to dollars catches things dollars hide

Six illustrative trades, made up for the arithmetic, with a planned risk of $100 each (1% of a $10,000 account). Pip value is $10 per lot.

1. EURUSD long, stop 8 pips, 1.25 lots, +12 pips: +$150, +1.5R
2. GBPUSD short, stop 10 pips, 1.00 lot, -10 pips: -$100, -1.0R
3. EURUSD long, stop 6 pips, 1.67 lots, +3 pips: +$50, +0.5R
4. EURUSD short, stop 8 pips, 2.50 lots, -8 pips: -$200, -2.0R
5. USDCHF long, stop 12 pips, 0.83 lots, +18 pips: +$149, +1.5R
6. GBPUSD long, stop 10 pips, 1.00 lot, +10 pips: +$100, +1.0R

In dollars the day is +$149, four winners of six, average win $112 against an average loss of $150. That looks like an ordinary slightly positive week.

In R, trade 4 is a -2.0R loss on a trade planned for 1R. The stop was hit exactly where it should be, so the problem isn't the stop. The lot size was double, 2.50 where 1.25 would have been right. In the dollar column it's one of two losses. In the R column it stands out immediately.

That's what R is for. Dollars say what happened, and R says whether it was what you planned. A column of results that mostly sit near -1R and a few bigger numbers is a sizing leak.

[FXS HongKong Scalper]

Trade 4 is the giveaway. Risking $200 on a trade planned for $100 looks like an ordinary loss in dollars but jumps out as -2R. I would add a planned R column next to the actual one so oversized trades stand out even when they win. A win of +2R on a trade sized at double risk is still a rule break, and dollars alone would hide it.

[TradeLock]

A column that dollars and R both miss is how long after your last losing
close you entered this trade. Revenge trading is mostly a timing problem
rather than a sizing one, so a time column lets you test it instead of
guessing. Log the gap in minutes, then split your trades into entries
opened within 30 minutes of a loss and everything else, and compare the
average R of the two groups. In a lot of journals the short-gap group is
clearly worse even when position size never changed, because the setup
quality dropped instead. That turns "wait a bit after a stop" into a
rule you can check later with numbers rather than a feeling you had at
the time. Thirty minutes is only a placeholder; the useful number is
the one your own data shows.

[PTScalper]

A column that dollars and R both miss is how long after your last losing
close you entered this trade. Revenge trading is mostly a timing problem
rather than a sizing one, so a time column lets you test it instead of
guessing. Log the gap in minutes, then split your trades into entries
opened within 30 minutes of a loss and everything else, and compare the
average R of the two groups. In a lot of journals the short-gap group is
clearly worse even when position size never changed, because the setup
quality dropped instead. That turns "wait a bit after a stop" into a
rule you can check later with numbers rather than a feeling you had at
the time. Thirty minutes is only a placeholder; the useful number is
the one your own data shows.

From my point of view revenge trading is mostly psychological problem. Thats why it is important to handle stress carefully.

[Fairman]

R is only as good as the initial stop. Record it at entry, in the same row as the entry price, and don't overwrite it when you move the stop. Planned risk in dollars is lots times stop distance in pips times the pip value. R is then the result, including commission and swap, divided by that planned risk. If you move the stop to breakeven and get taken out for +$2, the R is +0.02R, not zero, and not +1R. Keeping R tied to the original risk means the numbers stay comparable between trades, even when management differs, which is the point of the column.

[Fairman]

Two R columns are a useful extra. One is planned R, what the result would have been if the risk had been exactly 1%. The other is actual R, using the dollars and the risk you really took. For trade 4, planned R at the intended size would have been -1.0R and actual R is -2.0R. The gap between them is the sizing error, and adding up that gap over a month gives a figure for what sloppy sizing cost, in R and in dollars. Seeing it as one number, such as -3.5R over 40 trades, tends to get attention that a vague sense of being a bit loose with size doesn't.

[Fairman]

A short list of columns that make the review easier: date and time, symbol, direction, setup name, entry price, initial stop, target, lots, planned risk in dollars, exit price, result in dollars after costs, result in R, and a one line reason. Thirteen columns, and most are filled in at the time of entry. The ones that matter most for later analysis are the setup name, which lets you sort by strategy, and the initial stop, which lets you compute R without guessing. Everything else can come from the platform's history export. If a column never gets used in a review, remove it.

[Fairman]

A weekly check in the sheet takes two minutes. Add the R column, count the trades with a loss bigger than 1.1R, and look at their dates and lot sizes. In the example above that gives one trade out of six, a 17% rate of oversized losses, and the cause is on the same line. If it's zero for several weeks, good. If it isn't zero, the next step is to look for a pattern: a time of day, a symbol, the trade after a loss. Having the lot size and the time in the same row makes the pattern easy to spot. A second filter is whether the oversized loss was bigger than the stop would explain. A 1.3R loss on a 1R stop usually means slippage, while a 2R loss with a clean fill means size.