Position sizing, explained
"How much should I buy" has a standard answer among traders, and it is not a feeling: decide what a losing trade may cost first, and let the math tell you the size. Here is how the formula works, a worked example, and what it deliberately leaves out.
The core idea: risk is chosen, size is derived
The common approach fixes risk per trade as a small percentage of the account, often around 1 to 2 percent. The point is survival across a losing streak: at 1 percent risk, ten losses in a row cost roughly 10 percent of the account, which is recoverable. Sizing by conviction instead ("I really like this one") makes the worst loss land on the largest position, which is exactly backwards.
The formula
Worked example: a $1,000 account risking 1 percent, buying at $1.00 with a stop loss at $0.90. The risk budget is $10. The stop sits 10 percent below entry, so the position is $10 ÷ 0.10 = $100, which is 100 units. If the stop is hit, the loss is the planned $10 and nothing more. Our position size calculator does this arithmetic for you.
The stop distance is doing the work
Notice what the formula implies: a tighter stop allows a larger position for the same risk, and a wider stop forces a smaller one. A trade with a stop 2 percent away supports a position five times larger than one with a stop 10 percent away, at identical dollar risk. This is why experienced traders talk about where the stop belongs before they talk about size, and why volatile assets naturally produce smaller positions: their sensible stops are wider.
It also explains when leverage shows up honestly: if the formula outputs a position larger than the account (which happens with very tight stops), executing it requires borrowing. That adds liquidation risk on top of the planned stop, a different and larger kind of risk than the formula models.
What the math ignores
The formula assumes the stop fills exactly at the stop price. Real markets do not promise that:
- Slippage and gaps. Fast moves and thin order books fill stops below the intended price. On volatile tokens the realized loss can be a multiple of the planned one.
- Liquidity. A position that is large relative to a pool's depth moves the price against itself both entering and exiting. Checking liquidity first (our token checker shows it per token) keeps the model honest.
- Fees. Trading fees, priority fees and spread all nibble at the edges, which matters most for small accounts and frequent trades.
Traders who size on volatile, thin tokens often compensate by treating the calculated size as a ceiling rather than a target.
Common failure patterns
- Sizing by conviction. Confidence and correctness are uncorrelated on any single trade; the formula exists precisely to protect you from your own certainty.
- Widening the stop after entry. That silently multiplies the risk the size was built on.
- Doubling after losses. Increasing size to win it back turns a survivable drawdown into an account-ending one; the arithmetic of recovery is brutal, since a 50 percent loss needs a 100 percent gain just to break even.
- Ignoring correlation. Five open positions in five Solana memecoins is closer to one large position than five independent ones; they tend to fall together.
Where to go from here
The calculators page runs the formula live, and the sentiment index is useful context for the correlation point: when the whole market is risk-off, stops across correlated positions get tested together.