What is Monte Carlo Simulation?
A technique that runs thousands of randomized scenarios to estimate the range of outcomes a portfolio or plan might produce — and how likely each is.
Educational — not investment advice
Instead of a single "you’ll have $X" projection, a Monte Carlo simulation replays your plan thousands of times with randomized returns drawn from realistic assumptions. The output is a distribution: the odds of hitting a goal, the range of ending balances, the chance of running out of money.
It is widely used for retirement and goal planning because it captures the reality that returns arrive in an unpredictable order, not a smooth average.
The trap most people miss
The output is only as honest as its assumptions. Feed it too-rosy returns or a normal distribution that ignores fat tails, and it will confidently understate the odds of a bad outcome. A precise-looking probability can still be wrong.
Frequently asked about Monte Carlo Simulation
Why use Monte Carlo instead of one projection?
Because a single average-return projection hides sequence risk. Monte Carlo shows the range of possible outcomes and the probability of each, which is far more realistic.
Is a 90% success rate safe?
It means 1 in 10 simulated paths failed under the assumptions used. Whether that’s "safe" depends on those assumptions and your tolerance — it’s a probability, not a guarantee.
Related terms
In Tradune: project goal outcomes with a Monte-Carlo simulator.
Track what you actually own
Tradune puts every holding in one place — no brokerage login — and measures your return against a buy-and-hold SPY twin funded on your own dates.
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This definition is for educational purposes only and is not investment, tax, or financial advice. Concepts are explained in general terms; how they apply to your situation can differ. Always do your own research.