R multiples, explained

“I made $600 today” tells you almost nothing. Was that one contract or ten? Was the stop $50 away or $500? An R multiple answers the question dollars cannot: how much did this trade make or lose compared with what it risked. It is the single most useful unit a trading journal can record.

What R is

1R is the amount you planned to lose on a trade if your stop was hit. Every result is then expressed as a multiple of it.

Long 2 MES at 5,800 with a stop at 5,792. MES is $5 a point, so the risk is 8 points × 2 contracts × $5 = $80. That is 1R for this trade.

• Exit at 5,812 (+12 points): +$120, which is +1.5R.
• Stopped out at 5,792: −$80, which is −1R.
• Panic exit at 5,780, through the stop: −$200, which is −2.5R. That number should bother you more than the dollar figure does.

Why R beats dollars

It makes trades comparable. A +$300 trade on one contract and a +$300 trade on five contracts are not the same trade. In R, one might be +3R and the other +0.6R.

It survives changes in size. If you scale up after a good month, your dollar results jump even if your trading did not change. Your R results stay honest.

It exposes execution. Losses should cluster around −1R. A loss of −1.8R means the stop was moved, ignored or slipped badly. Count how many of those you have.

It turns your edge into one number. Average R per trade, called expectancy, says how much you make for every unit of risk you take.

Expectancy

A trader who wins 40% of trades at an average of +2R and loses 60% at an average of −1R has an expectancy of 0.4 × 2 − 0.6 × 1 = +0.2R. Over 100 trades at $100 risk, that is roughly +20R, or $2,000, before costs. Over 10 trades it is noise.

The second point matters as much as the first. A positive expectancy over 15 trades is not evidence of an edge. That is why Traquil’s Quil Score counts sample size as its own part, and why it reads 20 lucky trades as 20 lucky trades.

The R distribution

Plot every trade’s R as a histogram and you learn things an average hides. A healthy distribution for a stop-based strategy has a wall at −1R (losses stopped where planned) and a tail to the right (winners allowed to run). Common problems show up as shapes:

• Losses spilling past −1R: stops being moved or ignored.
• Winners bunched below +1R: taking profit early, often out of fear of giving it back.
• A spike at 0R: lots of scratched trades, which is worth a look on its own (see reading your win rate with break-evens).

Recording R properly

R needs one thing written down before the trade: the stop. If you log the stop after the fact, it tends to drift to wherever makes the trade look reasonable. Record the planned stop at entry, even if you later move it, because R is measured against the plan.

Some trades have no stop you can honestly reconstruct. Leave the risk blank for those rather than inventing one. A journal that derives risk from the result is just measuring the result twice.

If you size by risk, R also links straight back to position size: the position size calculator works out contracts so that 1R is the amount you chose.

R in Traquil

Enter a stop when you log a trade and Traquil records the result in R as well as in dollars, net of commission. Statistics shows your expectancy and the full R distribution, the Mistakes Tracker reports what each mistake has cost in R, and the backtest replay can size orders by risk so practice results are in the same unit.