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Monte Carlo.A range of outcomes, not a promise.

A backtest is one path through the past. Monte Carlo resamples its trading days into many simulated paths, so you can see how wide the outcomes could be under simulated conditions. It doesn’t show whether a strategy will make money.

Median outcome
−$4,277
5th percentile
−$10,533
95th percentile
+$2,401
Profitable paths
17%
Risk of ruin
100%
Cumulative P&L, 1,000 simulated pathsSample of 60 shown, simulated data
$0

A losing simulated strategy, drawn with the same simulator as the app. A range of outcomes under simulated conditions, not a forecast.

How to read it.

Each line is one way the same trading days could have come out in a different order.

  • Median outcome

    The path in the middle. Half of the simulated paths end above it and half below it.

  • 5th and 95th percentile

    How far the outcomes spread in each direction. The wider the fan, the more of the result could be luck.

  • Risk of ruin

    The share of paths whose drawdown reaches a limit you set, such as a prop firm’s max loss.

What it can’t tell you.

A simulation only knows what’s in the backtest it’s given.

  • Not a forecast

    It reuses the backtest’s own days. Anything those days never saw isn’t in it.

  • Not a profit

    A fan that rises only says the backtest’s days added up. It doesn’t show that a strategy will make money.

  • Only as good as the sample

    A short or overfit backtest makes the fan look better than it is.

It sits in the backtest’s report.

Run the backtest, then open Monte Carlo beside the results and the prop firm odds. It also runs on a List of trades you export from TradingView.

A backtest running in the app on simulated data: the stats and equity curve, the prop firm pass odds, then a Monte Carlo fan.A backtest running in the app on simulated data: the stats and equity curve, the prop firm pass odds, then a Monte Carlo fan.

Straight answers.

No. It shows a range of outcomes under simulated conditions, built from a backtest’s own results. Those results are hypothetical, and a simulation of them can’t tell you what will happen next.

Whole trading days by default, drawn at random with replacement. Runs of consecutive days or single trades are the other ways to do it, and each keeps and breaks different patterns.

Monte Carlo shows how an account’s equity could spread out. Pass odds run the same kind of simulation through one prop firm plan’s rules and count how many runs pass, fail or run out of time.

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From an idea to your chart

Describe it, test a strategy with simulations and your prop firm’s rules, then take it to TradingView.

  • Indicators and strategies in Pine Script
  • Backtests, Monte Carlo and prop firm rules
  • Deploy to TradingView