How to Use Risk of Ruin Calculator
The Risk of Ruin Calculator helps traders and investors estimate the probability that their account will fall to a ruin threshold given their trading parameters. Enter your strategy statistics and capital management settings, then choose a calculation mode to see the results.
- Select a Calculation Mode — Choose Simplified Formula for a fast analytical estimate, or Monte Carlo Simulation for a path-based probability distribution.
- Enter Win Rate — Input your historical or estimated win percentage (1–99%).
- Enter Avg Win and Avg Loss — These are expressed as R-multiples. For example, if your average winner is twice your average loser, enter 2 for Avg Win and 1 for Avg Loss.
- Set Starting Capital and Ruin Threshold — The ruin threshold is the account level below which you consider the account “ruined” (e.g., 50% of starting capital).
- Set Risk per Trade — The percentage of your current account risked on each trade.
- For Monte Carlo Mode — Also enter the number of trades per simulation path and the number of simulation runs (100–10,000).
- Read the Results — The Risk of Ruin Calculator displays the estimated ruin probability, risk level, expected value per trade, reward/risk ratio, Kelly position size, and for Monte Carlo mode, the estimated final balance range and worst drawdown.
Formula & Theory - Risk of Ruin Calculator
The Risk of Ruin Calculator uses two complementary approaches:
Simplified Formula Mode
Edge = (WinRate × AvgWin − LossRate × AvgLoss) / (WinRate × AvgWin + LossRate × AvgLoss)
Risk of Ruin ≈ ((1 − Edge) / (1 + Edge)) ^ CapitalUnits
CapitalUnits = floor((StartingCapital − RuinThreshold) / (StartingCapital × RiskPerTrade))
| Symbol | Meaning |
|---|---|
| WinRate | Probability of a winning trade (0–1) |
| LossRate | 1 − WinRate |
| AvgWin | Average profit expressed as R-multiples |
| AvgLoss | Average loss expressed as R-multiples |
| Edge | Normalized edge per trade |
| CapitalUnits | Number of full risk units between start and ruin |
Monte Carlo Simulation Mode
For each simulation run:
capital = StartingCapital
for each trade:
if random() < WinRate: capital += capital × RiskPerTrade × AvgWin
else: capital −= capital × RiskPerTrade × AvgLoss
if capital ≤ RuinThreshold: mark as ruin, break
Risk of Ruin = ruined_runs / total_runs
Kelly Criterion
Kelly Fraction = WinRate − LossRate / (AvgWin / AvgLoss)
A positive Kelly fraction indicates a positive expected value strategy. Risking more than half the Kelly fraction significantly increases drawdown and ruin probability.
Assumptions and Limits
The Risk of Ruin Calculator assumes independent trades with fixed fractional sizing, a constant win rate and payoff ratio, and no transaction costs. Real markets involve non-stationary statistics, correlation between trades, and execution imperfections. Use this tool for educational estimation and scenario analysis, not as a precise forecast of future performance.
Use Cases for Risk of Ruin Calculator
The Risk of Ruin Calculator is valuable for any trader, investor, or game theorist working with probabilistic outcomes and capital management:
- Trading strategy evaluation — Assess whether a strategy’s statistics (win rate, payoff ratio) combined with a risk-per-trade setting produce an acceptable ruin probability before committing real capital.
- Position sizing optimization — Compare different risk-per-trade percentages to find the balance between growth rate and safety.
- Kelly Criterion analysis — Use the Kelly output to understand the theoretically optimal position size and identify over-leveraged configurations.
- Monte Carlo scenario planning — Visualize the range of possible account outcomes after hundreds of trades, including worst-case drawdown scenarios.
- Risk management education — Understand how seemingly small differences in win rate or payoff ratio can dramatically shift the probability of ruin.
The Risk of Ruin Calculator provides a transparent, browser-based environment for exploring the mathematics of trading risk. Always combine quantitative estimates with sound trading discipline and professional advice.