Two traders both made $400 on a trade. One risked $100, the other risked $800. In dollars they look identical; in reality one made a great trade and the other a mediocre one. R-multiples fix that blind spot by measuring every trade in units of what you risked, not what you made.
What 1R is: your initial risk as the unit of measure
1R is the amount you put at risk when you enter a trade — the distance from your entry to your initial stop, multiplied by your position size, in account currency. It’s fixed at the moment of entry and never changes.
If you buy at 100 with a stop at 95 and size the position so that gap equals $200, then 1R = $200 for that trade. From there every outcome is expressed as a multiple of that unit:
- Hit your stop → −1R (you lost exactly what you risked)
- Exit at a $400 profit → +2R
- Exit at a $100 profit → +0.5R
- A slippage-widened stop that costs $300 → −1.5R
The dollar figure is irrelevant once you convert. What you’re left with is a clean number describing how the trade performed relative to the risk you took to get it.
Converting P&L to R-multiples across instruments
The conversion is one division: R-multiple = trade P&L ÷ initial risk (1R).
That single step is what makes R portable. A forex trade, a futures trade, and an equity trade all reduce to the same scale the moment you divide by their respective 1R. To do it accurately you need to know your initial risk precisely, which means defining your stop and size before entry — a discipline the risk-reward calculator enforces by making you set the stop and target that define R in the first place.
Log 1R at entry. Log the exit P&L at close. Divide. That’s the whole workflow, and it’s the foundation everything else builds on.
Why R makes trades comparable regardless of position size
Position size is the biggest distortion in a raw dollar journal. Trade bigger and every number inflates; trade smaller and your best setups look unimpressive. Dollars measure your size as much as your skill.
R strips size out entirely. A +2R trade is a +2R trade whether you risked $50 or $5,000 — the quality of the decision is captured, the size of the bet is normalised away. That’s what makes R the right unit for prop-firm traders specifically:
- You can compare a trade on a small evaluation account to one on a large funded account directly.
- You can pool trades across multiple accounts into one honest data set instead of letting your biggest account dominate the stats.
- You can size consistently — keeping 1R equal to a fixed percentage of each account keeps risk constant everywhere. The position size calculator does exactly this conversion, turning a fixed R into the correct lot for each account’s balance.
Expectancy as average R per trade
Once every trade is in R, your edge becomes a single number: the average R across all your trades. That’s expectancy expressed in risk units.
Expectancy (R) = average R per trade = total R ÷ number of trades.
Add up the R-multiples of your last 200 trades and divide by 200. If the result is +0.35R, you net roughly a third of your risk on an average trade — a genuine, size-independent edge. If it’s negative, no position sizing rescues it. This is the same expectancy concept, but computed straight from your R-log with no separate win-rate and average-win bookkeeping. The trading expectancy guide connects the two views in detail.
Building an R-multiple journal and distribution
The average R is the headline; the distribution of your R-multiples is the story. Plot how often each outcome occurs — how many −1R, −0.5R, +1R, +2R, +3R trades you’ve had — and your system’s real character appears.
What the shape tells you:
- A cluster of losses tighter than −1R means your stops are holding as designed.
- Losses regularly worse than −1R mean slippage, gapping, or — most often — moving your stop against yourself.
- A long right tail of large winners is the signature of a trend system; a tight cluster of small winners marks a mean-reversion one.
The distribution also exposes whether your edge depends on a couple of outlier winners. Remove your top two +R trades — if the system goes negative without them, you have a fragile edge, not a robust one. Building this by hand is tedious, which is why Shibiki auto-journals every fill and plots your R-distribution automatically, so the shape of your edge is visible without spreadsheet upkeep.
Common mistakes: moving stops and corrupted R
The R system only works if 1R is honest. Two habits corrupt it:
- Moving your stop wider mid-trade. The instant you widen a stop, your realised loss exceeds your logged 1R, and every R-multiple on that trade is a lie. A −1R that’s really a −1.8R poisons your average and hides your worst habit inside a clean-looking number. If you must adjust, log the actual risk taken, not the original.
- Redefining R after the fact. Some traders quietly recompute R to make a bad trade look better. R must be fixed at entry, full stop. A journal that lets you edit historical risk is a journal that lets you lie to yourself.
This is the strongest argument for automated journaling: when the platform records your entry, stop, and size at the moment of the fill, 1R is captured before emotion gets a vote. Shibiki also pushes hard risk limits down to the broker, so the stop that defines your R is enforced at the account level — you can’t quietly widen it into a −3R disaster, which keeps both your account and your R-log honest.
Related: R-multiple · Position size calculator · Trading expectancy