Risk of Ruin
The probability that a trader will lose enough capital to be unable to continue trading, calculated based on win rate, position size, and risk-reward ratio.
What Risk of Ruin Means
Risk of ruin is the statistical probability that a series of losses will reduce a trading account below a usable threshold, rendering the trader unable to continue. The concept was formalized for financial markets by Ralph Vince in *Portfolio Management Formulas* (Wiley, 1990) and applies to any system where a finite bankroll faces repeated probabilistic outcomes. According to ESMA data (2018), between 74% and 89% of retail CFD accounts lose money — suggesting that ruin probability is systematically underestimated by individual traders.
How It's Calculated
The classic formula for fixed-fraction betting:
R = ((1 - Edge) / (1 + Edge)) ^ Units
Where:
- Edge = (Win Rate × Average Win) - (Loss Rate × Average Loss)
- Units = Account Size / Risk Per Trade
This produces a single probability. But real trading involves changing conditions, correlated losses, and psychological thresholds that the formula ignores.
Why It Matters for Traders
A strategy with a positive expected value can still have a high risk of ruin if position sizes are too large. The gap between "profitable on average" and "survivable in practice" is where most traders fail.
Key factors that increase ruin probability:
- Higher risk per trade (the single most impactful variable)
- Lower win rate without compensating R-multiples
- More trades over time (longer exposure to variance)
- Correlated trades (sector concentration amplifies drawdowns)
Monte Carlo vs. Formula
Static formulas assume identical, independent trades. Monte Carlo simulation runs thousands of randomized trade sequences to produce a distribution of outcomes, showing not just the average case but the worst 5% (P5) and best 5% (P95) scenarios. As Nassim Taleb noted in *Fooled by Randomness* (Random House, 2001), "path dependency makes the difference between theoretical profitability and practical ruin."
How to Reduce Your Risk of Ruin
1. Lower your risk per trade — the single most effective lever; reducing from 5% to 2% can cut ruin probability by 60–80%
2. Improve your risk-reward ratio — wider targets relative to stops
3. Define your personal ruin threshold — the drawdown that would make you stop
4. Test your parameters with simulation before trading live
Use the Risk of Ruin Calculator for a quick estimate, or download RangeSight for full Monte Carlo analysis with real market data.
Key Takeaway
The probability that a trader will lose enough capital to be unable to continue trading, calculated based on win rate, position size, and risk-reward ratio. Use RangeSight Studio's Monte Carlo simulator to model risk of ruin with 10,000 simulated paths and real market volatility.
This explains the concept.
But how risk of ruin affects your specific strategy depends on your parameters, position sizing, and market conditions.
Test your strategy to see how consistent it actually is → Run survival test
See the full distribution with real market data
10,000 Monte Carlo paths. P5/P50/P95 scenarios. Real ticker volatility.
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Risk of Ruin vs. Kelly Criterion: Which Should Guide Your Position Sizing?
Risk of ruin tells you whether you'll survive. Kelly tells you how fast you could grow. Understanding both is essential for sizing positions correctly.
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A backtest shows what did happen. Monte Carlo shows what could happen. The difference determines whether your strategy survives real trading.
Fixed Fractional vs. Kelly Sizing: Which Position Sizing Method Wins?
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