Almost every blown account in retail trading is a Position sizing failure, not a signal failure. The trade idea may have been fine; the size that was put behind it was not. Risk management is what lets a real but modest edge eventually compound; without it, even a great strategy dies on a single bad sequence.
Stop loss
A Stop loss is a price level you commit to in advance: if the market trades there, you exit, no debate. The stop's job is not to be a prediction β it is to cap the damage of any single bad call. Place it where being right would mean your thesis is wrong: behind a structural level, beyond an indicator threshold, somewhere price simply should not go if the idea holds.
Position sizing
Once a stop is decided, sizing is arithmetic. Pick a fixed percentage of your account you are willing to risk per trade β 0.5% to 2% for most retail accounts β and compute how many units of the asset put exactly that much money between entry and stop. If the stop is 2% away and you risk 1% of equity, your position is half your equity in notional terms (before leverage).
This is the only correct order of operations: choose risk per trade, choose stop distance, derive position size. Sizing first and stopping wherever leaves you is how accounts die.
The R vocabulary
Traders measure outcomes in R β multiples of the initial risk. A trade where the stop was $100 below entry and the exit was $200 above is a 2R winner. A trade stopped out exactly at the stop is a -1R loser. Talking in R instead of dollars normalises across position sizes and lets you compare a 100-trade record meaningfully: a system that averages +0.3R per trade across hundreds of trades is making money even if the dollar amounts look small.
Reflection
What is the most you have ever lost on a single trade, as a percentage of your account at the time? Was that loss inside your plan, or did sizing run ahead of risk?
Further reading
Deeper dives on this topic from our blog (English).
- Position sizing for crypto traders: the 1% rule revisitedPosition sizing for crypto traders: the 1% rule, ATR-based sizing, Kelly fraction, and why the equities-era rules need adjusting for 24/7 volatility.
- Risk of ruin: the math that decides whether you survive a losing streakRisk of ruin explained: how losing streaks threaten a trading account, what drives the probability of ruin, and how position sizing keeps it near zero.
- Win rate vs risk-reward: why a 90% win rate can still lose moneyWin rate vs risk-reward ratio explained: why win rate alone is meaningless, how expectancy combines the two, and why high-win-rate strategies often blow up.