Trading risk management is the set of rules that decide how much you lose when you are wrong. It is not about predicting the market. It is about ensuring that being wrong repeatedly โ which every approach does โ leaves you with enough capital and enough composure to keep trading the edge you believe you have.
Almost everything written about trading concerns entries. Almost everything that ends trading accounts concerns size. A strategy with a genuine edge and reckless sizing loses money; a mediocre strategy with disciplined sizing survives long enough to be improved. This page covers the arithmetic that governs that: how to size a position, what R-multiples are and why they make results comparable, the relationship between win rate and reward-to-risk, how losing streaks scale, and why drawdowns are harder to recover from than they look.
None of this tells you what to trade. It tells you how much.
Fixed-fractional position sizing
The standard approach is to risk a fixed percentage of the account on each trade. The position size then falls out of the stop distance:
Position size = (Account balance ร Risk %) รท (Stop distance ร Value per unit)The stop comes from the chart. The risk percentage comes from your plan. The size is the output โ never the input.
Worked example, forex. A $10,000 account, 1% risk, a 25-pip stop on EUR/USD at $10 per pip per standard lot:
- Risk amount: $10,000 ร 0.01 = $100
- Loss per lot: 25 ร $10 = $250
- Position size: $100 รท $250 = 0.40 lots
The same account, a wider stop. A 60-pip stop on the same pair:
- Risk amount: $100
- Loss per lot: 60 ร $10 = $600
- Position size: 0.17 lots
The dollar risk is identical in both trades. Only the size changed, because only the stop changed. That is the entire mechanism, and it is what separates position sizing from guessing.
The arithmetic differs by instrument because the value per unit differs โ gold moves $100 per lot per dollar of price, indices move by the point, USD/JPY's pip value depends on the exchange rate. The lot size calculator handles the conversion, with dedicated pages for gold, EUR/USD and the NASDAQ 100.
One practical note: add spread and expected slippage to the stop before you divide. On a 12-pip stop, a 1.5-pip spread is over a tenth of the trade's risk.
R-multiples
An R-multiple expresses a result as a multiple of what you risked. Risk $100 and make $250, and the trade is +2.5R. Risk $100 and lose it, and the trade is โ1R.
This matters more than it first appears. Currency amounts are not comparable across trades, because a $500 win on a large position and a $500 win on a small one represent very different performance. R-multiples normalise for size, which lets you:
- Compare trades taken at different account balances
- Compare a gold trade with a EUR/USD trade
- Add up a strategy's results without size distorting them
- See whether your winners are actually larger than your losers
Expectancy is the average R across a sample:
Expectancy (R) = (Win rate ร Average win in R) โ (Loss rate ร Average loss in R)A positive expectancy means the strategy makes money over enough trades. A negative one means no amount of position sizing saves it โ sizing determines how fast you lose, not whether you do.
Win rate and reward-to-risk
These two numbers are linked by arithmetic. For a strategy where losses are 1R, the break-even win rate is:
Break-even win rate = 1 รท (1 + reward-to-risk)| Reward-to-risk | Break-even win rate |
|---|---|
| 1:1 | 50% |
| 1:1.5 | 40% |
| 1:2 | 33.3% |
| 1:3 | 25% |
| 1:5 | 16.7% |
This is a mathematical identity, not a claim about any strategy. It says that a system taking 2R winners only needs to be right a third of the time to break even โ and that a system taking 0.5R winners needs to be right two-thirds of the time just to stand still.
The practical use is diagnostic. If you know your average win and loss in R from your own records, you can compute the win rate you need and compare it with the one you have. What no article can tell you is what win rate your strategy achieves; that number exists only in your own trade history.
How losing streaks scale with risk
This is the calculation most traders skip, and it is the one that decides whether an account survives.
The number of consecutive losses that takes you to a given drawdown depends only on your risk per trade:
| Risk per trade | Losses to โ10% | Losses to โ20% | Losses to โ50% |
|---|---|---|---|
| 5% | 3 | 5 | 14 |
| 2% | 6 | 11 | 35 |
| 1% | 11 | 22 | 69 |
| 0.5% | 21 | 45 | 138 |
Streaks of six or eight losses occur in strategies that are perfectly sound over a large sample โ that is what randomness around a positive expectancy looks like. At 5% risk, an ordinary streak is an account-threatening event. At 1%, it is a bad fortnight.
This is also the arithmetic that governs prop firm evaluations, where the drawdown limit is set for you. A 5% daily loss limit and 1% risk per trade means five losses ends your day; the FTMO calculator and the other firm pages set out the limits each one imposes.
The right way to choose your risk percentage is to find your strategy's worst historical losing streak โ backtesting gives you that โ and pick a risk level where that streak is survivable with room to spare. Not the average. The worst.
Drawdown recovery is asymmetric
A loss and a gain of the same percentage are not equal, because the gain works on a smaller base:
Required gain = 1 รท (1 โ drawdown) โ 1| Drawdown | Gain needed to recover |
|---|---|
| 10% | 11.1% |
| 20% | 25% |
| 30% | 42.9% |
| 50% | 100% |
| 70% | 233% |
The asymmetry accelerates. A 20% drawdown is an inconvenience; a 50% drawdown requires doubling the remaining capital to get back to level. This is the strongest argument for conservative sizing, and it is arithmetic rather than opinion.
Rules that follow from the arithmetic
Risk a fixed percentage, not a fixed lot size. A fixed lot size means the risk varies with every change in stop distance, which is the opposite of control.
Size from the stop, never the reverse. Choosing a size first and fitting a stop to it is the most common way traders take far more risk than they intended โ particularly on tight setups like a flag pattern, where a small stop implies a large position.
Cap total open risk. Three positions at 1% each is 3% at risk, and if they are correlated it is closer to a single 3% position. Long EUR/USD and short USD/CHF is nearly one trade.
Reduce size when volatility expands. A wider range means a wider stop means a smaller position for the same risk. Keeping the size constant while the range doubles silently doubles the risk.
Decide the stop before entering. A stop moved after entry is not a risk control.
Know your daily and weekly stop. A limit on how much you will lose in a day exists to interrupt the sequence of decisions that follows a bad morning.
Measuring your own numbers
Every figure that matters here โ expectancy, average win and loss in R, worst losing streak, whether results hold up when volatility rises โ is specific to you and cannot be read off an article. Getting them requires recording trades in a form that supports the comparison.
At minimum, log for each trade: the instrument, the setup, the stop distance, the risk in percent, the result in R, and the market conditions. Fips's trading journal records trades in R and groups them by setup, and account analysis shows the distribution of outcomes rather than the average โ which matters, because a strategy with a good average and a long tail of large losses is not the same as one with a good average and a tight spread, though both look identical in a summary.
Once you have thirty or forty trades, the questions become answerable: which setups carry the results, whether your winners are large enough for your win rate, and what your real worst streak has been. Those answers change what you should risk per trade. Backtesting a rule before trading it gives you the same information without the tuition fee.
Frequently asked questions
How much should I risk per trade?
There is no universal figure, but the arithmetic constrains it: at 2% risk, eleven consecutive losses cost 20% of the account. Most traders working from a defined strategy use between 0.5% and 1%, and the sound way to choose is to find your strategy's worst losing streak and pick a level where that streak leaves you able to keep trading.
What is an R-multiple?
A result expressed as a multiple of the amount risked. Risking $100 and making $300 is +3R; losing the $100 is โ1R. It makes trades comparable across different position sizes, instruments and account balances.
Is a high win rate better than a high reward-to-risk ratio?
Neither is better on its own โ they trade off. A 1:3 reward-to-risk needs only 25% winners to break even; a 1:0.5 ratio needs 67%. What matters is whether your actual pairing of the two produces positive expectancy, which you can only compute from your own records.
Why does a 50% loss need a 100% gain?
Because the gain is calculated on the reduced balance. Losing half of $10,000 leaves $5,000, and getting back to $10,000 from there means doubling. The asymmetry is why avoiding large drawdowns matters more than producing large gains.
Does position sizing matter if my strategy has no edge?
No. Sizing determines how quickly a negative-expectancy strategy loses money, not whether it does. Sizing keeps you solvent long enough to find out whether you have an edge; it cannot create one.