Stress-test your strategy with Monte Carlo simulation
A single backtest is one path through history. Monte Carlo resamples your trades thousands of ways to reveal the range of outcomes — risk of ruin and percentile equity curves — you could realistically face.
Stress-test your strategy with Monte Carlo simulation, explained.
A backtest shows you one sequence of trades — the one that happened. Monte Carlo simulation takes the trades from that backtest and resamples them many times to estimate the distribution of outcomes, not just the single historical path.
VolatiCloud supports three methods — trade-shuffle, bootstrap, and parametric — and reports risk of ruin alongside percentile equity curves. It answers the question a single profit number can't: how bad could a realistic run of this strategy get?
From idea to a running bot.
Monte Carlo turns one historical outcome into a probability distribution you can reason about.
Start from a backtest
Run a backtest first — its trade ledger is the input the simulation resamples.
Pick a method
Choose trade-shuffle (reorder the trades), bootstrap (resample with replacement), or parametric (model the return distribution).
Run thousands of iterations
The simulation runs many iterations — up to 10,000 on Pro and 50,000 on Enterprise — to build the outcome distribution.
Read risk of ruin
Review risk of ruin and percentile equity curves to understand the downside, not just the average case.
Built for the way you trade.
Monte Carlo is for traders who size positions by worst-case, not best-case.
Risk managers
Quantify the probability of a drawdown that would force you to stop — before it happens with real money.
Position sizers
Use percentile equity curves to choose a stake size you can survive a bad streak with.
Strategy validators
Separate strategies that were genuinely robust from ones that got lucky on a single historical path.
- Trade-shuffle, bootstrap, and parametric methods
- Risk-of-ruin estimation
- Percentile equity curves
- Up to 10,000 iterations on Pro, 50,000 on Enterprise
- Built directly on your backtest's trades
- Reveals downside a single backtest hides
Frequently asked questions.
Why isn't a backtest enough?
A backtest is a single path — the exact order of trades that happened. Monte Carlo resamples those trades many ways to show the range of outcomes you could face, which is what you need to size risk.
Which methods are supported?
Three: trade-shuffle (reorders the trade sequence), bootstrap (resamples trades with replacement), and parametric (models the return distribution). Each stresses the strategy differently.
What is risk of ruin?
Risk of ruin is the estimated probability that a strategy draws down far enough to wipe out or force you to stop. Monte Carlo estimates it across thousands of resampled runs.
How many iterations can I run?
Up to 10,000 iterations on Pro and up to 50,000 on Enterprise. More iterations give a smoother, more reliable outcome distribution.
Related capabilities.
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