CFDs and forex are complex instruments and come with a high risk of losing money rapidly due to leverage. Risk disclosure

Risk of ruin in trading

This page explains what risk of ruin is, which inputs change it, and how to use the simulator to see the range of outcomes a fixed-risk strategy can produce.

Extrade Pakistan editorial team ·

On this page
  1. What risk of ruin means
  2. The inputs that drive risk of ruin
  3. Run your own numbers
  4. How to read a simulation
  5. Formula versus simulation
  6. What the model leaves out
  7. Fixed fractional and fixed lot
  8. Using the result in your risk plan
  9. Frequent questions

What risk of ruin means

Risk of ruin is the probability that a trading account falls to a level you define as "ruined" before it recovers. Ruin does not have to mean a zero balance. Most traders set it as a drawdown they would not accept, for example the point at which they would stop trading or could no longer follow their plan.

A drawdown is the fall from the account's highest value to a later low. Risk of ruin asks how likely it is that the drawdown reaches your chosen limit at some point during a series of trades.

The answer is never zero for a strategy that can lose. Leveraged forex and CFD trading can lose money fast, and a strategy with a positive edge can still hit a deep drawdown through an ordinary losing streak.

start1% per tradeDD −9%2% per tradeDD −17%5% per tradeDD −41%10% per tradeDD −72%100 identical trades, 40% wins, reward 1.5 × risk
The same sequence of trades at different risk per trade. With zero expectancy, higher risk does not add profit; it only deepens the drawdowns (DD). Illustrative example: made-up numbers for learning, not real prices or a broker's conditions.

The inputs that drive risk of ruin

Risk of ruin trading models usually rest on a small set of inputs:

Win rate and R:R together set your expectancy, the average result per trade in R. If expectancy is negative, ruin is only a matter of time, whatever the risk per trade. If it is positive, the risk per trade decides how deep the swings get on the way. See Trading expectancy and Break-even win rate.

Risk per trade is usually the strongest lever. With the same win rate and R:R, a larger risk per trade makes the account swing harder in both directions. That raises the chance that a normal losing streak crosses your ruin level.

Run your own numbers

Typical result (median)1,245
Bad case (worst 10%)879
Good case (best 10%)1,678
Runs that lost half the balance0%
Average deepest drawdown18.9%
Expectancy per trade0.13 R

500 random runs of the same rules. This is a model of arithmetic, not a forecast: real markets have costs, slippage and streaks the model ignores.

The simulator is a Monte Carlo model of a fixed-risk strategy. Monte Carlo means the model generates many random sequences of wins and losses from your win rate and R:R, applies your risk per trade to each, and records what happens to the balance in every run. The result is a spread of possible outcomes, not a single forecast.

What the output shows:

Treat the output as a model. It assumes every trade is independent and that wins and losses are always the same size in R. Real trading is less tidy.

How to read a simulation

A practical way to use the risk of ruin calculator:

  1. Enter win rate and average R:R from your own records, not from what you hope to achieve. A trading journal gives you these figures.
  2. Set the ruin level to the drawdown at which you would really stop or change your approach.
  3. Run the simulation at your current risk per trade and note the share of runs that reach ruin.
  4. Lower the risk per trade and run it again. Compare the drawdown range and the ruin share.
  5. Lower the win rate a little to test what happens if your edge is smaller than your records suggest.

The last step matters. Win rates measured over a short sample are uncertain. If a small drop in win rate makes the ruin share jump, your plan has little margin for error.

Formula versus simulation

Classic risk of ruin formulas give a single probability from win rate, payoff and risk size. They are useful for intuition, but they assume fixed trade outcomes and often an endless series of trades. A simulation lets you set a finite number of trades, a specific ruin level and compounding rules, and shows the whole distribution, which a single figure hides.

Neither method tells you what your next trades will do. Both describe what your inputs imply if those inputs are accurate and stay stable.

What the model leaves out

Real-world risk of ruin is usually higher than a simple model shows. Common reasons:

Fixed fractional and fixed lot

How you size positions changes the shape of the outcomes. With fixed fractional sizing, you risk the same share of the current balance, so position size shrinks after losses and grows after wins. This slows the fall during a losing streak. With a fixed lot, the money at risk stays the same as the balance falls, so each loss takes a larger share of what is left. The comparison is covered in Fixed fractional vs fixed lot.

Methods such as the Kelly criterion suggest a size from your edge, but they depend heavily on accurate inputs and can produce very deep drawdowns. None of these methods guarantees a profit.

Using the result in your risk plan

Risk of ruin is one input to a wider plan. Useful links:

More tools are on the Calculators page.

Frequent questions

What is risk of ruin in simple words?

It is the chance that your account falls to a loss level you have defined as unacceptable before it recovers.

Does a positive expectancy mean zero risk of ruin?

No. A positive expectancy lowers the long-run risk, but a losing streak can still push the account to your ruin level, especially with a large risk per trade.

Which input changes risk of ruin the most?

Usually risk per trade. With the same win rate and R:R, a smaller risk per trade narrows the drawdowns and lowers the simulated ruin share.

Is the simulator a forecast?

No. It is a model of random trade sequences based on your inputs. It shows a range of possible outcomes, not what will happen.

Why is my real drawdown deeper than the simulation?

Real trading includes costs, slippage, gaps, correlated positions and changes in behaviour, which a simple model does not include.

Where do I get a reliable win rate and R:R?

From a record of your own closed trades over a meaningful sample. Short samples can be misleading, so test lower values in the simulator too.

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