Calculate the modelled probability of hitting a ruin threshold from win rate, payoff and risk per trade.
How this is calculated
The model runs repeated fixed-fractional trades using win rate, payoff ratio and risk per trade
Each trade multiplies the balance by (1 + risk × payoff) on a win or (1 − risk) on a loss
Risk of ruin is the share of simulated paths that fall to the ruin threshold within the trade horizon
Worked example
Win rate 45%, payoff ratio 2.0, risk 2% per trade, ruin threshold a 50% decline, 200 trades.
Each win adds 4% and each loss subtracts 2% of the running balance.
The output is the percentage of simulated sequences that reach the 50% decline before the horizon ends.
Understanding risk of ruin
Risk of ruin estimates the probability that a sequence of trades reaches a defined loss threshold before a horizon ends. This page runs a Monte Carlo simulation — five thousand independent paths of the trade count you specify — and reports the share of those paths that hit the threshold. The random draw is seeded, so the same inputs always return the same figure rather than shifting by a few tenths on every keystroke.
The assumptions are strong and worth stating before the number is used for anything. Outcomes are treated as independent, the win rate and payoff ratio stay constant across the entire horizon, every trade risks the same fraction of the current balance, and there are no costs beyond what is already inside the payoff ratio. Real trading breaks all of these at times, particularly around volatility regime changes, when win rates and payoff ratios move together and positions stop being independent of one another.
The sensitivity table is the part of this page most worth reading. Because fixed-fractional losses compound, the relationship between risk per trade and modelled ruin is not linear: going from 1% to 2% typically does far more than double the probability, and by 5% many otherwise positive-edge configurations show substantial ruin rates over a few hundred trades. A positive edge does not protect an account from ruin if the position size is large enough — it only guarantees the average path drifts upward, and a ruined path never gets to participate in that average.
Edge per trade, shown alongside the probability, is the expectancy of the configuration in R. When it is negative, ruin at a long enough horizon is effectively certain and the only question the model answers is how quickly. When it is positive, the ruin probability is driven almost entirely by the risk fraction and the horizon length: longer horizons give more opportunities to encounter the losing streak that reaches the threshold, so extending the trade count never reduces the figure.
Choose the ruin threshold deliberately. Fifty percent is the conventional default, but for a funded or evaluation account the relevant threshold is the firm's maximum drawdown, which is often much shallower and therefore much easier to reach. The average worst drawdown figure gives the complementary view: how deep a typical path went even when it survived, which is frequently the more useful number for deciding whether a size is tolerable in practice.
Treat the whole output as a property of the model rather than a forecast about your account. It is most valuable comparatively — as a way to see what changing one input does — and least valuable read as a single authoritative percentage.
Frequently asked questions
Is risk of ruin a prediction?
No. It is the output of a model built on the assumptions you enter, including a constant win rate and independent outcomes.
What ruin threshold should I use?
Any decline you consider unacceptable — commonly 50% of the account, or the maximum drawdown limit of a funded account.
Why does small extra risk change the result so much?
Fixed-fractional losses compound. Larger per-trade risk deepens each losing streak, so the threshold is reached in far more simulated paths.
Does it account for correlated positions?
No. The model treats trades as independent, so simultaneous correlated positions are not represented.