Calculator
A stop-loss order caps the downside: the calculator prices the maximum loss if the stop is hit, plus a gap-through scenario where the fill lands twice the stop distance — common around earnings and news events.
Maximum Loss at Stop
$1,200.00
Stop Analysis
If the stop is hit, you lose $12.00 per share on 100 shares — $1,200.00 total — 2.40% of your $50,000 account. The stop sits 8.0% from entry, and the position consumes 8.0% of its own value at the stop. In a gap-through (stop fills at 2× the distance), the loss doubles to $2,400.
*Assumes the stop order executes at the stop price. Gaps through news and earnings can fill worse. Educational only, not investment advice.
A stop loss is a pre-committed exit: an order to sell when a position moves against you to a price you chose while you were still thinking clearly. Its value is not the order itself but the decision it encodes — the maximum loss defined before emotion enters the trade. Traders who enter without a stop are not avoiding downside; they are agreeing to find out what their downside is in real time, at the worst possible moment. The disciplined alternative is to price the loss first: dollars per share, dollars total, and what that total represents as a share of the portfolio. For US retail investors the stop loss is most useful at the trade-management level: protecting a swing position, capping a speculative sleeve, or enforcing an exit rule on a position whose thesis has broken. The calculation is simple — shares times the distance from entry to stop — but its implications run deep, because the stop's placement determines how many shares the same risk budget can support, and therefore how large the position becomes. This calculator prices any stop: the exact dollar loss if it is hit, the loss as a percentage of the position and of the whole account, and a gap-through scenario that doubles the stop distance — the realistic worst case around earnings and overnight news that market orders never see coming.
The per-share risk is entry minus stop for a long position, stop minus entry for a short. Total loss at the stop multiplies that distance by the share count. The stop distance expressed as a percentage of the entry price is the loss the position itself suffers; the total loss expressed as a percentage of the portfolio value is what actually threatens the account's compounding. A 100-share position stopped 8% away loses 8% of the position — but if that position is a third of a small account, the account takes a nearly 3% hit from a single trade, and a streak of three such losses is already a 9% drawdown that takes a 10% gain just to repair. The gap-through scenario addresses the failure mode the standard number hides: stops trigger at the stop price but fill at the next available price, and across earnings, economic releases, or weekend news that next price can be far worse. Modeling the fill at twice the stop distance — a deliberately conservative stress, not a forecast — shows what the trade costs in the version of events where everything gaps. The honest read: the normal-case number is what you plan around; the gap number is what you insure against with position size. Both numbers together are the difference between a stop you can trust and a stop that quietly carries more risk than the plan admits.
A stop placed at a round number or an arbitrary percentage below entry is decoration, not risk management. The stop should sit where the original reason for the trade is no longer true — below a support level, below a moving structure, past a pattern's invalidation point. That placement also dictates the size: a wider structural stop supports fewer shares under a fixed risk budget, a tighter one supports more but must survive the stock's normal noise. The stop answers 'where am I wrong?' and the position-size formula answers 'how much am I wrong for?' in that order, every time.
Traders naturally think in position percent — 'I'm down 8% on the trade' — but the account only feels the total dollars. A 2% account-risk stop survives a brutal ten-loss streak at roughly 18% drawdown; a 5% account-risk stop on the same streak approaches 40%, a hole that takes a 67% gain to fill. The account-percent readout in this tool exists to enforce exactly that arithmetic: any stop costing more than 1–2% of the account is not a trade idea, it is a portfolio event, and most retail accounts cannot absorb a run of portfolio events and still compound.
The most common stop-loss failure is not placement but post-entry management: a price approaching the stop tempts the trader to lower it 'just a little' to avoid being taken out. Every widening converts a defined loss into a larger undefined one, and the pattern compounds — the stop that gets moved once gets moved again. Professional discipline is the opposite: stops only ever move toward the trade in favor, never against it. If the original stop is about to be hit, that is information the thesis was wrong, and the exit is working exactly as designed.
For any trade holding through an earnings date or a weekend with major scheduled events, run the gap-through scenario and ask whether 2× the stopped loss is still affordable to the account. If it is not, either reduce the size, use options to cap the actual downside, or move the entry until after the event. The gap scenario is the honest price of overnight exposure — paying it in position size beforehand beats discovering it in the fill afterward.
A stock that routinely swings two percent in a day will stop out a one-percent stop as noise before the trade can work. Check the typical daily range, then place the stop outside it — a structural level a normal fluctuation cannot reach. The resulting wider stop means fewer shares at the same dollar risk, which is not a penalty but the trade telling you its true size for your account. If that size feels too small to matter, the trade is mismatched to the account, not the stop.
As an account grows, a fixed dollar stop becomes a shrinking percentage of it — and a stop sized to last month's account silently risks more of this month's. Re-run the percentages whenever the account value moves materially, and size new trades against the current number. The same logic applies after drawdowns: a 10% account loss means the same dollar stop now risks 11% more of what remains. Sizing against the live account is the habit that keeps risk constant in the only currency that matters.
Jordan wanted to hold a swing long into earnings with a $1,500 stop on a $50,000 account — 3% of account risk. The gap-through scenario showed the overnight version of that trade could cost $3,000, or 6%. He cut the position size in half, kept the same stop level, and held through the report with the real worst case back inside his 2% limit. When the stock gap down 9% overnight, the stopped fill cost $1,400 instead of the $2,800 the original size would have carried.
Priya kept being stopped out on stocks that then ran in her direction. Measuring the gap between her entries and stops showed most sat two to three percent away on stocks swinging two percent a day. Moving stops to structural levels below support widened the distance, cut the share counts the risk budget allowed, and let her trades survive normal pullbacks. The account-level math stayed identical — same dollar risk per trade — but the win rate improved because the stops finally sat where being right stopped being possible.
Tom shorted at $84 with a $89 stop and 300 shares, which the calculator showed was a $1,500 risk — exactly 2% of his $75,000 account. Two losing short trades would have cost 4% under his old sizing habit; at the new size, the same two losses cost the same dollars but the third and fourth losses remained equally survivable. When the short finally worked, it worked at the planned reward; the difference was that the losing ones no longer compounded into a crisis. The arithmetic did not change his direction — it changed what his direction could cost.
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Financial Chaos Analyst
Ivy Sinclair-Wren is a Financial Chaos Analyst covering investing, AI, wealth psychology, and the emotional consequences of opening finance apps during market crashes. Based in Melbourne, she specializes in demystifying the US tax code and helping users navigate the intersection of spreadsheet logic and human irrationality.