Risk management in six steps

Risk management means deciding before every trade the most you'll lose. The charts show why the risk per trade alone decides whether a good strategy makes money in the end.

9 min read Last checked: 2026-09-24

Risk management sounds like a corporate department, but at its core it's a single habit: before every trade you decide the most you'll lose, and you stick to it. If you don't, you can lose your account even with a good strategy. If you do, you get through bad phases too.

This page brings the individual pieces together into one plan. Each step has its own lesson if you want to go deeper.

Step 1. How much you risk per trade

Most experienced traders risk 0.5 to 2 percent of their account per trade. With €10,000 that's €50 to €200. It sounds small, and that's the point: even ten losses in a row then cost only part of the account, not all of it. More in the one percent rule.

The chart below shows why the level matters so much. Three traders make exactly the same 36 trades. The strategy is slightly profitable. The only one who ends up losing is the one risking 10 percent per trade. Big swings eat up gains, because a 50 percent loss needs a 101 percent gain afterwards. The drawdown lesson shows this in more detail.

Same hit rate, three different risk levels 36 made up trades, 13 of them winners with double the gain, 23 losers. That's a slightly profitable strategy. With 1% risk per trade the account ends at €10,266, with 10% at €9,483, although the trades are identical.

Step 2. Where your stop belongs

Your stop loss belongs where your idea stops being right, for example below an important low. It doesn't belong wherever your preferred amount happens to be reached. A good guide for the distance is the usual daily swing, the ATR. If your stop is tighter than a normal daily move, it often gets hit for no reason. More in setting a stop loss.

Step 3. How big the position gets

Only now does it follow how much you buy. The formula is simple: allowed loss divided by the distance to the stop.

An example: Anna has €10,000 and risks 1 percent, so €100. She wants to buy a stock at €50, with her stop at €47.50. The distance is €2.50. €100 divided by €2.50 gives 40 shares, so €2,000 invested. If the stop is further away, she buys fewer. Her risk always stays at €100. More in calculating position size.

Step 4. Whether it's worth it at all

A trade where you risk €100 to make €100 needs a hit rate above 50 percent just to break even. If you risk €100 to make €200, about 33 percent is enough. With fees and spread the threshold is higher, as the chart shows.

How often you need to be right Hit rate needed for a strategy to break even, depending on the reward to risk ratio. The upper line includes costs of 0.1R per trade, a tenth of the risk.

The ratio of possible gain to possible loss is called the reward to risk ratio. Together with the hit rate it gives the expected value, what you win or lose per trade on average. If it isn't positive after costs, even the best risk management won't help.

Step 5. Limits for the day and the week

Many accounts don't break on one bad trade but on what comes after: the attempt to win the loss back straight away. That's why many traders also set limits for the whole day and the week.

After two losses in a day, that's it for today.
At most 3 percent loss per day and 6 percent per week. Once the limit is reached, no more trading until the next period.
After a month with a 10 percent loss, the position size is halved until half of it has been recovered.

More in overtrading and revenge trading and when to stop.

Step 6. Keeping the whole account in view

Five trades with 1 percent risk each are only five small risks if they have nothing to do with each other. If you buy Bitcoin, Ethereum and three other coins at the same time, you really have one big trade with 5 percent risk, because these often fall together. The correlation lesson shows this. A simple rule: the risk of all open positions together stays below 5 percent.

Leverage doesn't change these rules, it just makes them more important. With leverage the provider can close your position by force before your stop kicks in. Then the loss is no longer in your hands. More in liquidation.

What happens even with a good plan

Even a strategy that makes money over many trades has bad phases. The last chart shows 25 runs of the same strategy, just in a different order. Some are clearly ahead after 100 trades, the worst is at a loss. When you're in a phase like that, you don't know whether the strategy has stopped working or it's just bad luck. That's why you need rules set in advance.

The same strategy in 25 different orders Each line is the same made up strategy with 45% winners, 1.5R gains and 1% risk, just in a different random order over 100 trades. At the end the best run sits at €14,793, the worst at €8,546.

A short list before every trade

Where is my stop, and why exactly there?
How much do I lose in euros if it's hit, including fees?
Does that amount fit my limit per trade, per day and for all open positions?
How big is the possible gain compared to that?
Would I make this trade if I hadn't had a loss today?

The answers belong in your written plan and your trading journal. Both are available as templates to download.

Summary

Decide before every trade the most you'll lose, usually 0.5 to 2 percent of the account.
Position size comes from the allowed loss divided by the distance to the stop.
Too much risk per trade can turn even a good strategy into a loss.

Did you get it?

Anna risks €100 and her stop is €2.50 below the entry. How many shares does she buy?

40 shares, because €100 divided by €2.50 is 40.

What hit rate do you need, without costs, at a reward to risk ratio of 2 to 1 to break even?

About 33 percent.

Why are five crypto trades with 1 percent risk each often one big risk?

Because cryptocurrencies often fall together, so the five trades behave like one with 5 percent risk.

Sources and further reading

ESMA, warnings and information on the risks of CFDs and leveraged products. View source ↗
Ralph Vince: The Mathematics of Money Management, 1992.
J. L. Kelly: A New Interpretation of Information Rate, Bell System Technical Journal, 1956.