Risk of Ruin

Risk of Ruin Calculator for Monte Carlo trading survival odds

Run Monte Carlo trading simulations to estimate risk of ruin, drawdown risk, and realistic outcome distributions based on your win rate, R-multiples, and risk per trade.

Built for traders and prop firm candidates who want to control drawdowns and protect capital.

Know your risk of ruin before you increase position size

Risk of Ruin is the probability that your account hits a predefined failure level — such as a prop firm max drawdown or a personal equity cutoff. This calculator shows how win rate, reward-to-risk (R), and risk per trade combine to shape your long-term survival odds.

See how an edge can still fail when risk per trade is too aggressive — and where drawdown risk becomes unacceptable.

Understand how win rate, average win/loss (R), and compounding risk interact to produce very different survival probabilities.

How this Risk of Ruin Calculator works

Short walkthroughs on running Monte Carlo simulations and interpreting risk of ruin, drawdowns, and probability distributions.

7 min
Monte Carlo basics

Monte Carlo trading simulation explained

See how thousands of randomized trade sequences create a realistic range of equity outcomes and survival odds.

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6 min
Reading results

How to read risk of ruin & drawdown results

Learn how to interpret ruin probability, drawdown percentiles, and final equity distributions without relying on a single average.

Watch tutorial
8 min
Risk sizing

Choose a safer risk per trade

Compare different risk % settings to find a level that keeps ruin probability and drawdown risk within your limits.

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Key features of the Monte Carlo Risk of Ruin Calculator

Everything you need to stress-test a strategy’s survival odds, drawdowns, and outcome ranges — without exposing any trade-by-trade calculations.

Monte Carlo simulations

Run thousands of randomized trade sequences from your win rate, average win/loss (R), and risk per trade to see the full range of possible futures.

Risk of Ruin probability

Estimate the percentage of simulations where equity falls below your chosen ruin threshold — useful for personal risk limits and prop firm max drawdown rules.

Drawdown analysis (avg + percentiles)

View average, median, and 95th- and 99th-percentile max drawdowns to plan for normal conditions and worst-case variance.

R-multiple based modeling

Model performance in R (reward-to-risk) instead of dollars, making the analysis portable across markets, account sizes, and instruments.

Fixed fractional risk with compounding

Simulate realistic equity paths where each trade risks a fixed percentage of current equity — capturing compounding during growth and contraction.

Customizable ruin threshold

Define your own failure level (for example, a max drawdown limit or minimum equity level) to match your rules and risk tolerance.

Outcome distribution & key metrics

Get core metrics like expectancy (R), probability of finishing profitable, equity outcome percentiles, and risk ratios (including Sharpe/Sortino) from the simulation results.

Side-by-side scenario comparison

Compare two different setups (win rate, R, risk %, trade count, and ruin level) to choose the safer approach before you scale capital.

Works for any strategy & market

Use it for forex, futures, crypto, or stocks — any strategy where you can estimate win rate, average win/loss in R, and risk per trade.

Use risk of ruin insights with other Trading Risk Lab tools

Turn survival probabilities into practical position sizing, planning, and rules.

Risk of Ruin → Position Sizing Calculator

Use the simulator to choose a risk % that keeps drawdowns and ruin probability under control, then size each trade precisely with the Position Calculator.

Risk of Ruin → Trading Journal planning

Make sure you don't forget any trade details by logging them in the Trading Journal.

Risk of Ruin → Projections & trade scenarios

Stress-test different plans and trade scenario ideas to make sure they don’t push you into high drawdown or high ruin-probability territory.

FAQs: Risk of Ruin, drawdowns, and Monte Carlo simulations

Quick answers about risk modeling, assumptions, and how to use the results.

No. This is a statistical estimate based on your inputs (win rate, average win/loss in R, and risk per trade). Real trading includes changing market conditions, execution, and human factors. The simulator shows probability distributions across many possible equity paths — a guide for risk management, not a guarantee.
If your edge changes, your real outcomes will differ from the simulation. The calculator assumes win rate and average win/loss stay constant for the modeled period. Re-run the simulation whenever your stats update to keep the risk of ruin estimate relevant.
This calculator is designed for fast in-browser analysis. There is no built-in export feature here, so for record-keeping you can screenshot results or copy key metrics into your journal, then rerun scenarios whenever your inputs change.
Choose a ruin level that represents your real failure point. For personal accounts, many traders use a remaining-equity threshold such as 40–60% (a 40–60% drawdown). For prop firms, set the threshold to match the maximum drawdown rule (for example, 80% remaining equity = 20% max drawdown). The best setting is the one you would actually stop trading at.
Use more trades to model longer horizons (for example 200–500 trades). Use more iterations to stabilize results and reduce randomness (often 2,000+ runs). Start with your typical sample size and increase iterations if you want smoother probability estimates.
Risk of Ruin is the probability of hitting your failure threshold (a binary outcome: ruin or not). Max Drawdown describes how deep the worst peak-to-trough decline gets (the magnitude of pain). Together they help you size risk realistically: ruin tells you how often you might fail, drawdown tells you how severe the ride can be.

Ready to calculate your Risk of Ruin?

Run Monte Carlo simulations to understand survival probability, drawdown risk, and realistic outcome ranges — then make smarter position sizing decisions.