Risk of Ruin Calculator

Risk of ruin (RoR) is the mathematical probability that your trading account will experience a drawdown large enough to be considered 'ruined' — whether that means losing 50% of the account, 100%, or any threshold you choose. Unlike win rate alone, RoR captures the combined effect of your edge, your payoff ratio, and how much capital you risk per trade. A trader with a positive win rate can still face near-certain ruin if position sizes are too large.

The standard trading-industry formula is RoR = ((1 − E) / (1 + E))^U, where E is your edge per unit risked (E = win rate × payoff ratio − loss rate) and U is the number of full-risk losses your account can absorb before hitting the ruin threshold (U = ruin threshold % ÷ risk per trade %). If E ≤ 0, ruin is certain (RoR = 100%). This formula is exact for even-money payoffs and is the universally-used approximation for unequal payoffs (Ralph Vince lineage).

Risk per trade is the most powerful lever in the RoR formula — far more sensitive than edge. Cutting your per-trade risk in half roughly squares the base of the exponent, causing RoR to plummet. For example, a system with edge E = 0.375 has near-zero RoR at 1% risk (U = 100 → base^100 ≈ 0) but roughly 2% RoR at 20% risk (U = 5 → base^5 ≈ 0.019). This is the key insight Ralph Vince’s experiment with PhD holders demonstrated: even a 60% win rate system can blow up accounts when sized aggressively.

Professional traders typically aim for a risk of ruin below 1%, with many targeting below 0.5%. A 5% RoR is considered high for a live account — it means you expect to blow up your ruin threshold once in 20 similar runs. As a rule of thumb: keep risk per trade at 1–2% of capital, maintain a payoff ratio of at least 1.5:1 with a 50% win rate (or 1:1 with a 55–60% win rate), and your RoR will typically be below 1%.

Edge per R (also called expectancy in R-multiples) is the average profit or loss per trade expressed as a multiple of the amount you risk. It equals: edge per R = win rate × payoff ratio − loss rate. A positive value means the system is profitable per unit risked on average; a value at or below zero means eventual ruin is certain regardless of position sizing. It is the single most important number for evaluating a trading system’s quality because it combines both win rate and reward-to-risk in one dimensionless figure.

The ruin threshold defines what "ruin" means to you. Setting it at 100% means complete account loss; 50% means you treat a 50% drawdown as ruin even though half the capital remains. A tighter threshold (smaller %) reduces U (effective capital units), which raises RoR dramatically. For example, with a 60% win rate and 1:1 payoff at 10% risk per trade: RoR at a 100% ruin threshold is 1.73%, but at a 50% threshold it rises to 13.2% — the same system, but a tighter definition of failure.

No. Win rate must be combined with payoff ratio to compute the true edge: a 60% win rate with a 0.5:1 payoff gives edge = 0.6×0.5 − 0.4 = −0.1 (negative — certain ruin). A 40% win rate with a 2:1 payoff gives edge = 0.4×2 − 0.6 = 0.2 (positive — survivable). The payoff ratio and risk per trade must both be considered. This is why traders use RoR rather than win rate alone to judge account safety.

Both quantify how position sizing interacts with edge, but they answer different questions. The Kelly criterion tells you the OPTIMAL risk fraction to maximize long-term capital growth: f* = win rate − loss rate / payoff ratio. Risk of ruin tells you the SURVIVAL probability at any chosen risk fraction. Most professional traders use a fraction of Kelly (e.g. half-Kelly) as their position size, then verify that the resulting RoR is acceptably low — the two tools complement each other.

The closed-form RoR assumes: (1) fixed-fractional sizing — the same percentage of current capital is risked every trade; (2) independent, identically-distributed trades — past results don’t affect future ones and your edge is stationary; (3) a two-outcome model — every trade is either a full win or a full loss with no partial exits; (4) infinite horizon — the probability of ever being ruined, not within a fixed number of trades; and (5) costs excluded — no commissions, spread, slippage or taxes. Violations of these assumptions (especially correlation and regime change) mean the true ruin probability is higher than the formula suggests.

When risk per trade is very small (e.g. 0.1%), U = ruin threshold / risk = 100 / 0.1 = 1000. Raising any base less than 1 to the 1000th power gives a number so close to zero that it rounds to 0%. This is mathematically correct: with a positive edge and a very small per-trade risk, the probability of ever hitting the ruin threshold converges to zero over an infinite time horizon. In practice, 0% means 'vanishingly small', not literally impossible.

Not in the infinite-horizon closed form used here. The formula ((1−E)/(1+E))^U depends only on edge and capital units — not on the number of trades. This is because it computes the probability of EVER being ruined over an unbounded sequence of trades. The number of trades input is included because the shared engine also computes SQN and projected expectancy, which do depend on sample size. A finite-horizon formula (gambler’s ruin with a target) would depend on trade count, but this calculator uses the infinite-horizon form.

Use Monte Carlo when you have the actual distribution of your trades (not just averages), when your strategy is likely path-dependent, or when you suspect correlation between consecutive trades. The closed-form RoR assumes independence and uses only average win/loss — it can significantly understate real ruin probability for strategies that cluster losses (e.g. trend-following during choppy markets). Monte Carlo replays thousands of randomised trade sequences from your actual return distribution and estimates RoR as the fraction that hit the threshold. Think of this calculator as the fast, conservative lower bound; Monte Carlo is the realistic stress test.