Trading journal template: R multiples, expectancy and drawdown explained, and why the Kelly fraction is shown but never used

A trading journal that only records profit and loss in currency will mislead its owner within a month. A 400 win on a large position and a 400 win on a tiny one are not the same trade, and a run of currency figures cannot tell you whether the method is working or the sizing is. The fix is older than most retail platforms: measure every trade against the risk you took on it. This page explains the four statistics that follow from that, on one sample journal.

R: the risk you took

Van Tharp's short lesson on R defines the R-value as "the initial risk taken in a given position, as defined by one's initial stop loss", and the R-multiple as "the amount that you profited or lost in terms of your initial risk". His example: buy at 50 with a stop at 47, so R is 3 per share; exit at 47 and the trade is minus 1R; exit at 56 and it is plus 2R (source 1).

Two consequences. A stop that is hit should be about minus 1R plus fees; a loss much bigger than 1R means the market gapped through the stop or the trader did not honour it, and the journal will show which. And a trade sized so the risk is a fixed share of the account (one percent is a common ceiling in the trading literature, and the Bindler workbook's Guide says the workbook does not choose that for you) makes every R the same amount of money, so the R column and the currency column tell the same story.

Expectancy: the average R

Expectancy is the mean of all the R multiples in the journal: what one unit of risk returned on average, across wins and losses. A positive expectancy means the method made money per unit of risk over that sample; a negative one means it lost, whatever the win rate was.

The win rate on its own is the statistic most journals lead with and the one that says least. A 90% win rate with small wins and one large loss can carry a negative expectancy; a 40% win rate with wins of 3R and losses of 1R carries a strongly positive one. The Bindler workbook shows the decomposition beside the headline (win rate times average winning R, plus loss rate times average losing R) and checks that the two agree to the cent, so the reader can see which of the three levers moved.

Profit factor and drawdown: two different questions

Profit factor is gross profit over gross loss. It answers "how many units came in for each unit that went out" and it ignores how many trades it took. Maximum drawdown is the largest fall in the account from its running peak, as a share of that peak. It answers "how bad did it get on the way", which expectancy cannot, because expectancy has no memory of order. A journal needs both an average and a worst case.

The sample journal

The workbook ships with twelve illustrative trades on a 100,000 starting balance and a 1% risk share. Every statistic was recalculated with a formula engine and matched to an independent Python replica before listing (source 2).

• 12 closed trades, 8 wins, 4 losses, a 66.7% win rate.
• Net P&L 8,621.20; gross profit 10,156.00, gross loss 1,534.80, profit factor 6.62.
• Expectancy 0.856R. Average winning trade 1.78R, average losing trade minus 0.99R. Largest win 2.50R, largest loss minus 1.76R.
• Ending balance 108,621.20, a return of 8.62%, with a maximum drawdown of 1.35% of peak.
• The Kelly fraction on those figures is 0.48.

The finding in that block is the last line. Twelve trades with a 6.6 profit factor produce a Kelly fraction of 48% of the account per trade. Nobody should bet that, and the reason is in the sample size: twelve trades is not a distribution, it is an anecdote, and the largest loss of the next twelve will not be minus 1.76R forever.

What Kelly 1956 actually says

J. L. Kelly Jr's "A New Interpretation of Information Rate" appeared in the Bell System Technical Journal, volume 35, number 4, July 1956, pages 917 to 926 (source 3). It is a paper about a gambler with advance knowledge of a chance event, and it derives the fraction of capital that maximises the long-run exponential growth rate of that capital when the true probabilities are known. Kelly's own setting makes the point: a gambler who bet everything on a noisy channel "would probably be broke" in the long run "with probability one if he continued indefinitely", so he bets a fraction instead, and the optimal fraction depends on the true odds.

A trader does not know the true odds. The journal's win rate and average R are estimates from a small sample that drifts, and the full Kelly fraction assumes they are exact. That is why the Bindler workbook shows Kelly with its Guide's warning and never uses it to size a position: the position size the workbook suggests comes from your risk rule (balance times your risk share, divided by the distance to the stop, rounded to your lot), shown beside the size you actually took so you can see where you over- or under-sized.

Where the workbook fits

The Trading Journal and Position Sizing Workbook is one row per closed trade (entry, stop, exit, size taken, fees) with the risk-rule size, risk taken, net P&L, R multiple and running balance computed per row; a Stats sheet with the eighteen statistics above including the expectancy decomposition; an Equity sheet with balance after every trade, running peak and drawdown; room for 200 trades; and a Guide. Live formulas, no macros, no locked cells, Excel and Google Sheets. $19, one price.

It measures what you did. No signals, no forecasts, no backtests, no recommendation of what to trade. Trading involves risk of loss. Not investment advice.

Sources

1. Van K. Tharp, "A Short Lesson on R and R-Multiples", Van Tharp Institute: https://vantharp.com/wp-content/uploads/2018/06/A_Short_Lesson_on_R_and_R-multiple.pdf

2. Bindler, Trading Journal and Position Sizing Workbook specification, Guide sheet and verification log (products/trading-journal/spec.json, build.py and verify.py), figures as listed 27 September 2026.

3. J. L. Kelly Jr, "A New Interpretation of Information Rate", Bell System Technical Journal 35(4), July 1956, pp. 917 to 926, https://doi.org/10.1002/j.1538-7305.1956.tb03809.x; reproduced text at https://www.princeton.edu/~wbialek/rome/refs/kelly_56.pdf

Last checked against the sources on 28 September 2026.