Position sizing turns a planned exit level into a quantity estimate. The calculation starts with two decisions: the amount you are willing to model as a loss if the assumed exit fills, and the distance from entry to that exit. Costs and contract units change the answer. A stop price does not guarantee an execution price, so the result is a planning estimate rather than a maximum-loss promise.
For a simple linear instrument with a one-unit multiplier, before costs:
Estimated quantity = chosen risk budget ÷ absolute entry-to-stop distance per unit.
If your cost estimate is expressed per unit, add it to the distance. If the contract uses a multiplier or a different quote currency, convert the move into the contract’s actual P&L units first. Inverse contracts need their own payoff formula; do not paste a linear quantity formula into an inverse contract.
Work one example from budget to quantity
Suppose a fictional $10,000 research account uses a user-chosen 0.5% planned-loss input for one paper example. That creates a $50 budget for the calculation. With a proposed entry at $100 and a planned long exit at $95, the adverse move is $5 per unit. Before costs, the estimate is $50 ÷ $5 = 10 units, or $1,000 notional at the assumed $100 entry.
Now enter an illustrative $0.04 per unit for the round trip. Estimated risk per unit becomes $5.04, so $50 ÷ $5.04 = 9.9206 units before any venue quantity rules. At exactly that unrounded size and the stated assumptions, stop-distance loss plus entered costs is $50. In practice, the usable quantity may need to be smaller after rounding, and a gap, partial fill or unmodeled charge can still produce a larger loss.
For a short, the planned stop is usually above entry. Calculate the adverse price movement for the side you are modeling, then verify the resulting P&L sign. Reject a zero distance or a stop on the wrong side; do not let an invalid input produce an infinite size or a positive loss budget.
Include the contract’s quantity increment
An exchange may require quantities to follow a specified increment, minimum or contract multiplier. CME’s educational example shows the same principle in futures terms: a 50-tick stop is $500 of modeled movement for one contract when each tick is worth $10, while a $5 tick value produces $250 per contract. Contract economics, not the chart’s display precision, determine the dollar move. Those are CME futures examples, not crypto venue specifications. Check the live market’s own contract and order rules before applying a size.
Here is a separate fictional linear-BTC sensitivity. With a $50 chosen budget, a $60,000 entry, a $57,800 planned stop and $20 of estimated total cost per BTC, the pre-rounded estimate is $50 ÷ ($2,200 + $20) = 0.02252 BTC. If this hypothetical contract used a 0.001 BTC increment, rounding down gives 0.022 BTC. The stated model then yields $48.40 of price loss plus $0.44 of cost, or $48.84. Rounding up to 0.023 BTC would model $51.06, above the $50 input. The 0.001 increment is invented for this example; it is not a claim about a current venue.
If the rounded quantity falls below the venue minimum, the calculation does not authorize you to increase it. Mark the setup as too small for that contract, choose another instrument only after checking its terms, or leave the example untraded. A calculator that omits multipliers, quote conversion, minimum quantities and step sizes is useful for learning the base arithmetic, but it is not an order-ready ticket.
Keep the stop estimate separate from the fill
The $48.84 result depends on a fill at the assumed $57,800 level. In a second hypothetical, suppose the same 0.022 BTC instead exits at $57,000 after a gap. The $3,000 entry-to-fill move creates $66 of price loss; adding the same $0.44 cost gives $66.44. That is a sensitivity example, not a forecast of how often a gap occurs.
Stop trigger, stop order, fill, partial execution and liquidation are different events. A fast market may fill beyond a trigger or fail to fill under the expected conditions. The CFTC’s advisory covers risks in virtual-currency spot, futures and options markets; it specifically warns that leverage in futures can amplify losses. Its regulatory authority over cash markets differs from its role in commodity derivatives, so do not treat the advisory as a universal venue rule.
For a perpetual position, margin is a collateral requirement, not the planned stop loss. Current Hyperliquid documentation, for example, distinguishes cross from isolated margin and describes its own asset-dependent leverage and liquidation rules. That is one venue’s documented system, not a formula for every exchange. A position can be liquidated before a planned stop under account-specific conditions. Recheck the exact contract, account mode, collateral and current margin tier; do not infer liquidation distance from this article’s quantity formula.
Stress the open book, not just one position
Three independent stop estimates of $50, $30 and $20 would sum to $100 if every stated stop filled at its assumed price. That arithmetic is a useful first ledger, but it does not describe a common market shock or account-wide worst case. The positions may share a driver, stops may fill beyond their triggers, and funding or margin rules may change the account result.
A simple shared-shock example makes the distinction visible. Imagine a fictional portfolio with 0.02 BTC spot at $60,000 and 0.5 ETH linear perpetual at $3,000. Apply a hypothetical 5% decline to each: BTC contributes a $60 price loss and ETH a $75 price loss. After illustrative costs of $1 and $2 respectively, the modeled scenario totals $138. The assumed shared crypto-market driver is just a scenario label. It is not a measured correlation, probability or forecast, and the two contracts can behave differently in real markets.
The open-position scenario risk ledger records the side, quantity, multiplier, entry and stress prices, costs, and shared-driver assumption in one CSV. It includes the fictional two-position example above. The per-position fields use this simplified linear arithmetic:
Price P&L = side sign × quantity × contract multiplier × (stress price − entry price).
Net scenario P&L = price P&L − estimated fees − estimated funding or carry.
The ledger does not estimate correlation, assign scenario probabilities, model liquidation or predict a worst case. Keep missing values blank or label them unknown; do not silently enter zero. For context, compare leverage with position size, then preserve your planned rule and later observations separately in the trading journal template. The position-size calculator remains a single linear estimate and does not perform this portfolio stress test.
A short pre-trade research check
Before interpreting a size estimate, record the capital unit and risk budget you chose, the stop convention, contract multiplier, quote currency, size increment, minimum quantity, entry and exit cost assumptions, and whether funding applies. Recalculate after conservative fee and fill assumptions, then test one or more shared market shocks across all open positions. If a key input is unavailable, keep it unknown and do not present the output as a complete risk figure.
The risk budget in these examples is an input selected for illustration, not a recommendation. The CFTC notes that losses on margined futures can exceed initial funds; crypto spot, futures and options also have product- and jurisdiction-specific risks. This article does not prescribe a percentage, identify a trade, or promise that a stop will cap loss. Sources were checked on 27 September 2026; venue rules can change, so verify the live contract before using its mechanics in research.