Free risk-of-ruin calculator with Monte Carlo simulation. Plug in your win rate, R-multiples, and risk per trade — see the actual probability of blowing up your account before it happens. Includes a prop firm mode that calculates the odds of hitting Apex, Topstep, or FTMO drawdown limits.
What "risk of ruin" actually means
Risk of ruin is the probability that your account drops below a defined failure threshold at some point during a sequence of trades. For a retail trader, that threshold is usually a drawdown you wouldn't recover from psychologically — somewhere between -25% and -50% of starting capital. For a prop firm trader, it's a specific dollar amount: the firm's drawdown limit, which terminates the account when touched.
The number is more useful than expectancy alone because it accounts for variance. A system with positive expectancy can still blow up if you size positions too aggressively — bad sequences happen, and aggressive sizing amplifies them. Risk of ruin is what tells you whether your actual position sizing is survivable given your actual edge.
The calculator above runs 10,000 Monte Carlo simulations using your inputs. Each simulation plays out the trade sequence you specified, picking wins and losses randomly according to your win rate, and recording whether the account hits the ruin threshold at any point along the way. The percentage you see is the empirical ruin rate across all 10,000 simulated traders — a much more accurate estimate than the closed-form analytical formula most calculators use, which assumes constant trade outcomes.
How to use the calculator
% Drawdown mode (default)
Use this when you're trading your own capital and want to know the chance of hitting some personal ruin threshold (typically 25-50% drawdown). Inputs:
- Win Rate — percentage of decisive trades that finish profitable.
- Reward:Risk — average win divided by average loss, expressed as ratio.
- Risk per Trade — percentage of starting account risked per trade.
- Account Size — your starting capital in dollars.
- Ruin Threshold — the drawdown level you consider catastrophic (default 30%).
- Trade Sample Size — how many trades to simulate (200 = roughly a year of active day trading).
Prop Firm mode
Use this when you're on a funded or evaluation account. Pick your firm + account size, and the calculator applies that firm's specific drawdown rules — trailing for Apex/Topstep/MFF (with each firm's lock-offset logic), static for FTMO. Enter your dollar risk per trade directly since prop firm sizing is dollar-based, not percentage-based.
Why prop firm mode matters: a $200-per-trade risk on a 50K Apex account isn't 2% of buying power — it's 8% of your $2,500 drawdown buffer. That's the math most traders skip when sizing on funded accounts, and it's why so many otherwise-profitable traders fail evaluations. The P&L Calendar's prop firm tracker tracks this in real time as you log daily P&L.
Reading the results
The calculator outputs five things:
- Probability of Ruin — the headline number. The percentage of simulated paths that hit the ruin threshold.
- Equity Curves — 50 sample paths drawn over each other. Green = paths that survived. Red = paths that hit ruin. Blue = median path. Dashed grey = ruin threshold line. The visual variance is the point.
- Median End — the middle outcome. Half of simulated traders ended above this; half ended below.
- Best 10% / Worst 10% — the 90th and 10th percentile final balances. The range between these is your realistic spread of outcomes.
- Average Max Drawdown — across all 10,000 simulations, the average of each path's worst peak-to-trough decline. This is the drawdown you should mentally prepare for, not the median outcome.
How to interpret your ruin probability
| Ruin Probability | Interpretation | Action |
|---|---|---|
| < 1% | Genuinely survivable — your edge and sizing are well-matched. | Maintain discipline; consider scaling slightly. |
| 1–5% | Acceptable for most retail traders. Some bad luck is expected over a career. | Workable. Tighten sizing if real capital is at stake. |
| 5–15% | Concerning. Roughly 1 in 10 traders with these parameters will blow up. | Reduce risk per trade by 30-50%. Re-run. |
| 15–40% | Dangerous. Even profitable systems blow up at this risk level. | Cut risk in half. Reconsider whether the edge is real. |
| > 40% | Catastrophic. You're statistically more likely to blow up than to succeed. | Stop trading these parameters. Rework the system. |
The numbers in this table assume reasonable trade counts (200+). Below 100 trades, ruin probability is often understated because there hasn't been enough time for a bad sequence to play out. Above 500 trades, you'll see ruin probability climb on any account with even slight negative expectancy — which is exactly the point.
Why even a profitable system can blow up
The most counterintuitive lesson from running these simulations is that positive expectancy doesn't guarantee survival. A 55% win rate with 1.5:1 R:R has positive expectancy (+0.275R per trade). It's profitable on paper. But if you risk 5% per trade, the simulator will show a 30%+ chance of ruin over 500 trades. The same system at 1% per trade shows less than 2% ruin probability.
The difference isn't the edge — it's the sizing relative to variance. Aggressive position sizing on a real edge converts statistical variance into catastrophic outcomes. The Kelly Criterion exists precisely to address this — it gives you the mathematically optimal risk per trade for any given edge. Most pros risk 0.25-1% per trade, which is dramatically smaller than what their edge would theoretically justify, because variance in real markets is worse than the math suggests.
The prop firm angle: if you're on a $50K Apex account with a $2,500 drawdown limit, your "ruin threshold" is 5% of the account. At $250/trade risk (sounds reasonable), you're risking 10% of your drawdown buffer per trade. The simulator will show a ruin probability above 30% for nearly any realistic edge. This is why most prop firm evaluations fail. Not because traders lack edge — because they size positions for their account balance, not their drawdown buffer.
Limitations of Monte Carlo ruin estimates
Three things this calculator can't model, and you should know:
1. Trade independence is assumed. The simulator treats each trade as statistically independent — your loss today doesn't affect your win probability tomorrow. In real trading, losses cluster (correlated market regimes, your own emotional state after a losing streak). Real ruin probabilities are typically slightly higher than the simulation suggests for this reason.
2. Win/loss sizes are fixed. The simulator uses your average win and loss, not the actual distribution. Real trades have variable sizes (occasional bigger winners, occasional bigger losers from slippage). Tail events can blow accounts in ways the simulator won't show. This is why even a 0.5% ruin probability isn't truly zero risk.
3. Position sizing is constant. Real traders often scale up or down with confidence — increasing risk on perceived hot streaks. This is exactly the behavior that turns a survivable system into a ruined account. The simulator assumes you stick to your stated risk per trade. Discipline failures aren't visible in the math.
What the calculator does well: it gives you a defensible baseline. If the math says you have a 25% ruin probability with constant sizing and independent trades, the real-world number is almost certainly higher, not lower. Use it as a floor, not a ceiling.
Worked examples
Example 1: The conservative retail trader
Inputs: 55% win rate, 1.5:1 R:R, 1% risk per trade, $25,000 account, 30% ruin threshold, 500 trades.
Expected result: ruin probability below 1%, median end around $40,000-50,000. This is what survivable looks like. Most profitable retail day traders cluster in this zone.
Example 2: The over-sized prop firm trader
Inputs (prop firm mode): Apex 50K, 48% win rate, 1.2:1 R:R, $400 risk per trade, 200 trades.
Expected result: ruin probability around 70%. With a thin edge (essentially break-even at +0.06R/trade) and $400 per trade representing 16% of the $2,500 drawdown buffer, the account is overwhelmingly likely to blow up before the edge can play out. This is what blows up most Apex evaluations — not a lack of edge, but position sizing that ignores variance. Cutting risk to $150 per trade brings ruin probability down significantly, but it stays elevated because the edge is genuinely marginal. The honest answer when both your edge is thin AND your sizing is tight isn't "trade smaller" — it's "find a better edge first."
Example 3: The high-frequency scalper
Inputs: 70% win rate, 0.6:1 R:R (small winners, larger losses on the wrong ones), 2% risk per trade, $10,000 account, 25% ruin threshold, 1000 trades.
Expected result: ruin probability around 5-10%. The high win rate masks a weak R:R; 1000 trades give variance enough chances to catch up. A "70% win rate" sounds bulletproof but isn't.
Frequently asked questions
What's the difference between risk of ruin and risk of drawdown?
Risk of ruin is the binary probability of hitting a specific failure threshold (e.g., -30% drawdown or a prop firm limit). Risk of drawdown describes the magnitude of expected drawdowns regardless of whether they hit the ruin level. This calculator reports both: the headline ruin probability and the average maximum drawdown across all 10,000 simulations.
Why 10,000 simulations instead of 1,000?
Statistical precision. 1,000 iterations is fast but produces noisy results — re-running the same inputs can give answers that differ by 1-3 percentage points. 10,000 iterations smooths that out to under 0.5 percentage points of variance between runs, which matters when you're comparing scenarios. Modern browsers handle 10,000 iterations in well under a second.
What inputs should I use if I haven't logged enough trades yet?
Use conservative estimates. Assume a win rate 5-10 percentage points lower than what you think you have, and an R:R slightly worse than your best backtest. Variance in real trading is always worse than your sample suggests. If even those conservative numbers show low ruin probability, you're probably fine. If they don't, reduce sizing.
Does this work for futures, forex, stocks, or crypto?
Yes for all of them, with one caveat: the simulator assumes independent trades, which is roughly true for day trading liquid futures and major forex pairs. Crypto and small-cap stocks have stronger correlation in adverse moves — if everything dumps at once, multiple "independent" positions can lose simultaneously. Treat the calculator's output as a floor for those asset classes.
Why does the ruin probability change between runs?
Monte Carlo simulation uses random sampling, so each run produces slightly different results. With 10,000 iterations the variance is small (under 0.5pp), but it's not zero. If you need to compare two scenarios precisely, run each multiple times and average — or just look at whether the numbers are in the same broad zone (under 5%, 5-15%, etc.).
Is this different from the Kelly Criterion?
Yes. Kelly tells you the mathematically optimal risk per trade to maximize long-term growth given an edge. Risk of ruin tells you the probability of failure at whatever risk per trade you've chosen. They're complementary: Kelly tells you where to size, risk of ruin tells you what happens if you size differently. Most professional traders use Half-Kelly or smaller for exactly this reason.
Can I use this for backtesting?
Yes. Plug in your backtested win rate and R:R to see if a strategy is statistically survivable before risking real money. Pair it with the Win Rate Calculator to first compute expectancy, then this tool to check ruin probability at your intended position sizing. A strategy with positive expectancy but high ruin probability is not actually tradeable — it's a paper edge.
