Risk of Ruin Calculator
Calculate the probability that an entered fixed-fraction, two-outcome model first reaches a defined drawdown within a finite number of trades. The recurrence aggregates every modeled win/loss state; it does not sample random paths.
What does this risk of ruin calculator measure?
It calculates the probability that modeled balance first reaches the entered drawdown threshold on or before the entered trade horizon. Each trade is either a fixed-fraction loss or a fixed-fraction win multiplied by the entered payoff ratio. The result is conditional model arithmetic—not the probability that a real account will fail.
- Ruin is a threshold you define, not automatically a zero balance.
- The finite horizon is part of the result; this is not an unlimited-trades formula.
- Half, entered and double-risk rows change only the risk assumption and are not recommendations.
Define the ruin event and trade model
Use one consistent gross-or-net basis for the entered win probability and payoff ratio.
Finite-horizon model result
Finite-Horizon Fractional Ruin model 1.1.0.
Risk-fraction sensitivity
Each row holds win probability, payoff, drawdown definition and trade horizon constant. The rows compare assumptions; they do not label a risk fraction safe.
| Scenario | Risk fraction | Ruin probability |
|---|
How to use the calculator
- Enter a win probability and average-win-to-average-loss ratio measured on one consistent basis. The page cannot verify the sample or its stability.
- Enter the fixed fraction of current modeled balance lost on a losing trade. Wins use that same fraction multiplied by the payoff ratio.
- Define ruin as a drawdown from starting balance and enter a finite number of trades. Both values are part of the probability statement.
- Read the entered-risk result and the half/entered/double sensitivity rows as conditional comparisons, not as safety labels or sizing advice.
How the finite-horizon recurrence works
The model starts balance at 1. A win multiplies it by 1 plus risk fraction times payoff ratio; a loss multiplies it by 1 minus risk fraction. Probability mass is grouped by trade count and number of wins, while any mass that first reaches the floor is absorbed as ruin.
This recurrence evaluates every reachable binary state within the entered horizon in IEEE 754 double precision. It therefore has no random seed or Monte Carlo sampling interval, but it remains only as valid as the fixed probability, payoff, independence and loss-size assumptions.
Worked examples
| Entered scenario | Derived output | Meaning |
|---|---|---|
| 100% win probability; positive payoff; 2% risk; 50% drawdown; 100 trades | 0% modeled ruin probability | Every modeled outcome is a win, so the lower floor cannot be reached. |
| Any win probability; 0% risk; 50% drawdown; 100 trades | 0% modeled ruin probability | Both balance multipliers equal 1 when risk is zero. |
| 50% win; 1.0 payoff; 2% risk; 50% drawdown; 100 trades | A deterministic finite-horizon probability | The result is specific to the 100-trade horizon and 50% drawdown definition. |
Model and execution limitations
- The result is conditional on fixed, independent, two-outcome assumptions; real trading can violate every one of them.
- The model does not include edge drift, serial dependence, changing risk, gaps beyond the fixed loss, fees, spread, financing, slippage or execution failure.
- A positive arithmetic edge does not prevent the entered drawdown threshold from being reached within the modeled horizon.
- Extremely small probabilities can fall below JavaScript double-precision resolution; the interface labels that condition instead of displaying a false exact zero.
- No output is labeled safe, risky, acceptable or recommended.
The CFTC cautions that hypothetical results have inherent limitations and that actual results can differ because of factors including spreads, commissions, liquidity and execution. The result on this page should be read within the narrower boundaries stated above.
Frequently asked questions
- A modeled balance first reaches or falls below one minus the entered drawdown threshold, measured from starting balance, within the entered trade horizon.
- No. It uses a deterministic recurrence that aggregates every reachable win-count state and absorbs probability mass when the floor is first crossed.
- No. The probability is explicitly bounded by the entered number of trades.
- Positive arithmetic expectancy is an average under the assumptions. Some modeled outcome sequences can still cross the entered drawdown threshold before the horizon ends.
- No. The fixed-fraction model is scale-independent. Balance is used only to display the monetary level represented by the ruin floor.
- They rerun the same model with half or double the entered risk fraction while holding the other assumptions constant. They are sensitivity comparisons, not recommendations.
- No. Enter probabilities and payoffs on a consistent basis and remember that gaps, costs and execution differences can make real outcomes worse or otherwise different.
- No. The output is conditional on a simplified model and does not assess suitability, data quality or future risk.
Method sources and provenance
- Jasiulewicz and Kordecki, finite-time ruin recurrence — Academic example of finite-time ruin probabilities determined through recurrence equations; this page uses its own disclosed two-outcome recurrence.
- CFTC trading-system advisory — Official caution about hypothetical results and actual execution differences.
Local calculation: Inputs are processed in the browser by the named versioned model. The page does not send entered balances, rates, probabilities or notes to a calculation API.
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