How Do You Calculate Position Size?

What is the formula?

Shares = (account × risk %) ÷ (entry − stop)

Stock example. A $25,000 account, 1% risk = $250, entry $47.50, stop $45.00, so the stop distance is $2.50. Size = 250 ÷ 2.50 = 100 shares, a $4,750 position — 19% of the account in exposure while risking 1% of it.

Forex example. A $10,000 account risking 0.5% = $50, with a 25-pip stop on EUR/USD where a standard lot pip is $10. Size = 50 ÷ (25 × 10) = 0.2 lots.

Options example. Risk is capped at the debit for a long option, so a $500 risk budget on a contract costing $1.85 is 500 ÷ 185 = 2 contracts, with $130 unused. Sizing in contracts is coarse, and rounding down is the correct direction.

Why does the stop come first?

Because the stop is a statement about where the idea is wrong, and the size is a consequence. Choosing the size first and then placing a stop where it fits is the same as deciding how much to lose and then deciding what to think.

It also explains why a wider stop is not automatically riskier. The $2.50 stop above allows 100 shares; a $5.00 stop on the same idea allows 50 shares, and both risk exactly $250.

What breaks the calculation?

Gaps. A stop is an instruction, not a guarantee. Overnight and event risk mean the realised loss can exceed the planned one, which is an argument for smaller size on anything held through an earnings report.

Correlation. Five 1% positions in the same sector are one 5% position wearing a disguise. Size against the correlated block, not the ticker.

Costs. Commission and spread come out of the same budget. On a $250 risk, $12 of round-trip cost is 4.8% of the risk before the trade moves.

Margin and buying power. Correct risk sizing can still be impossible to hold. A 19% exposure is fine on a cash account; leveraged instruments turn the same risk calculation into a much larger notional.

How does this connect to a track record?

The formal version of "size from the stop, not from conviction" is Kelly's: given an edge and a payoff, there is a finite optimal fraction of the bankroll, and exceeding it lowers long-run growth even though the edge is unchanged.^[1] Most traders should size well below it, which is what a fixed-fractional risk rule does in practice.

Regulators have reached the same conclusion from the other direction. ESMA capped retail CFD leverage in 2018 after national analyses found 74–89% of retail accounts lost money, with average losses of €1,600 to €29,000.^[2] The intervention was on the multiplier rather than on what anyone was trading, which is a regulator agreeing that size is the variable.

Sizing is what turns an R-multiple into money, and consistent sizing is what makes a record interpretable at all. A metric is a summary of a record, so it inherits every weakness of that record. Computed from trades selected after the fact, it is a number about the selection. kappi commits each trade before it resolves and publishes it on a Merkle-anchored log, so PnL, RME, correlation to SPX, mean R:R and trade count over 30, 100 and 200-day windows are computed over everything that was committed, losses included. $15/month to keep a record; reading one is free.