Two trades, both closed at plus 400 euros. The first risked 100 euros to a stop and made four times that. The second risked 800 euros and made half of it back before the trader got nervous and closed. Your P&L column shows two identical lines. Your account has just met its best trade of the month and one of its worst, and it cannot tell them apart.
The unit that tells them apart is R. One R is the amount you decided to lose if the trade went wrong. Measured that way, the first trade is +4R and the second is +0.5R. Every result your journal holds can be written in the same unit, and once it is, three things become visible that a currency column hides: the size of your losses relative to the plan, the drift in your position size after a loss, and the true shape of your edge.
What is one R?
Van Tharp's definition is short. R is your initial risk on a trade: the distance from your entry to your stop, times the size of the position. If you buy at 100 with a stop at 98 on 500 shares, R is 1,000. Close at 104 and the profit is 2,000, which is 2R. Close at 98 and the loss is 1R, exactly what you planned. Close at 95 because you moved the stop and the loss is 2.5R, which is not what you planned, and the number says so.
Every closed trade becomes an R-multiple. The mean of those multiples is your expectancy, in R per trade. The distribution of those multiples is the honest picture of what your trading does, because it is measured against the one thing you control at entry: how much you were prepared to lose.
2R
A 2,000 profit on 1,000 risked
Tharp's own example of the unit
31.2% vs 27%
Chance of above-average afternoon risk, after morning losses vs gains
1,082 CBOT T-bond futures traders, 1998 (Coval and Shumway 2005)
5%
Maximum daily loss in FTMO's challenge
Read on 26 August 2026; equals 5R at 1% risk per trade
Why does the euro figure lie?
Because a currency result mixes two decisions that have nothing to do with each other: how good the trade was, and how big it was. A 400-euro profit can be a clean 4R or a sloppy 0.5R. A 400-euro loss can be a planned 1R or a 4R disaster on a position four times too large. The P&L column reports the product of quality and size and throws away the factors.
Size is exactly the factor that moves when you are not watching. Coval and Shumway studied more than 5 million transactions by 1,082 traders in the Chicago Board of Trade Treasury-bond pit in 1998. Traders who had lost money in the morning were more likely to take above-average risk in the afternoon than traders who had made money: 31.2% against 27%. They placed more trades and built larger positions, and the afternoon prices they set reversed faster than the prices set by the morning winners. Their afternoon exposure had grown. Nothing in a dollar column would show why.
Kahneman and Tversky give the mechanism. In prospect theory, outcomes are judged as gains or losses against a reference point, and the value function is steeper for losses than for gains. A morning loss moves the reference point. The afternoon is spent trying to get back to it, and the fastest way to get back to it in currency terms is to trade bigger. In R terms, trading bigger changes nothing about the quality of the trade. It only changes the size of the number you will have to explain.
Distribution of closed trades by R-multiple, demo account
Illustrative demo data, 260 trades, share of trades in each bucket
Source: Socius Trades demo journal
What does an R distribution show that a P&L curve does not?
The chart above is illustrative demo data. Read the left tail first. Nine percent of trades closed below -1.5R. By definition, a trade that was planned at 1R of risk can only lose more than 1R if the stop was moved, skipped, or filled through a gap. Nine percent of the sample carries one of those three explanations. A P&L curve shows the same trades as a few bad days. The R distribution shows them as a habit with a frequency.
Read the right tail next. Nine percent of trades closed above +2R. Those trades are the edge. If the average of the whole distribution is positive, it is because that right tail is large enough to pay for everything to its left. Cut the winners early, as the disposition effect Odean measured pushes you to, and the right tail shrinks while the left tail stays. The euro total may still look acceptable for a while. The R distribution will show the shift immediately.
How does R connect to the rules you already trade under?
Prop-firm rules are written in percent of capital, which is R with the position size fixed. FTMO's two-step challenge, as read on 26 August 2026, sets a maximum daily loss of 5% of initial capital and a maximum loss of 10%. At 1% risk per trade, the daily limit is five full losses and the total limit is ten. At 0.5%, double that. At 2%, the daily limit is two and a half trades away at the open. None of those numbers can be read off a P&L column. All of them are one division away from an R column. FTMO is a trademark of its owner; Socius Trades is not affiliated with FTMO.
The same arithmetic applies to any account, funded or not. With a 45% win rate, any given run of six trades has about a 2.8% chance of being six losses in a row, which over a few hundred trades makes such a streak close to certain. Six times 1R is survivable. Six times 2R, after a morning loss and an afternoon of larger positions, is the situation Coval and Shumway measured in the pit.
What your journal would show
The following figures are illustrative demo data, not a real account.
A demo account with 260 closed trades has an expectancy of +0.12R. The average winner is +1.4R and the average loser is -1.1R, against a planned -1R. The journal's R view shows the -1.1 is not evenly spread: on the two currency pairs the average loser is -1.0R, on the index CFD it is -1.6R. The by-hour view shows the trades below -1.5R cluster after 15:00 Paris, and the daily trade list shows that the three worst of those days each opened with a loss. The trader did not decide to trade bigger after losses. The R column says that is what happened.
The biggest single euro profit of the quarter is also on the list: +0.4R, on a position three times the usual size. In currency it was the best trade of the period. In R it was an average trade that happened to be large. The journal shows both numbers side by side, and you can decide which one you want to be proud of.
You can see the same cut on your own history. Socius Trades imports your executed trades from cTrader or MetaTrader 4 and 5, computes the R-multiple of each one and shows the distribution, by instrument, by session, by hour and by day. Ask Socius AI, in plain language, what your average loser is in R by hour of the day. We look. We never touch.
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“Euros tell you what happened to your account. R tells you what you did.”
Trading involves risk of loss. Socius Trades is an analytics tool, not investment advice.