Are the results reproducible?

Yes. Each run stores a random seed, so the same inputs and seed reproduce the exact same outcome.

Normal vs. bootstrap — which should I use?

The normal distribution is simple and smooth; historical and block bootstrap resample real returns and better capture crashes and clustering.

Monte Carlo Simulation

Project a range of possible futures for your portfolio by simulating thousands of randomized return paths. Add contributions or withdrawals and see your probability of success.

Educational use only — not investment advice

This tool is for educational and informational purposes only and does not provide financial, investment, tax, legal, or accounting advice. Results are hypothetical and based on historical data and assumptions that may be inaccurate. Past performance does not guarantee future results. Consult a licensed professional before making investment decisions.

SimulationIntermediate

What is the Monte Carlo Simulation?

Estimate the range of outcomes your portfolio might experience using thousands of randomized return paths, with a probability of success.

Rather than a single forecast, the Monte Carlo Simulation generates thousands of randomized return paths to map the range of possible outcomes. Draw returns from a normal distribution or resample real history (bootstrap), add monthly or annual contributions or withdrawals, account for inflation, and define what 'success' means — ending above zero, hitting a target, or surviving withdrawals. Results are summarized as a probability of success, percentile bands, and an ending-balance distribution, and every run is reproducible via its stored seed.

How to use it

1Set your starting point: an initial balance, a time horizon, and either a historical portfolio or your own expected return and volatility.
2Add any cash flows (monthly or annual contributions or withdrawals), choose the number of simulations and the method (normal or bootstrap), and define what 'success' means.
3Run the simulation to see your probability of success, a percentile cone of outcomes, and the full range of ending balances across thousands of paths.

What you'll get

✓Probability of success
✓Median and percentile ending balances
✓Year-by-year percentile cone
✓Depletion probability
✓Ending-balance distribution

New here? See it in action

Will $100k + $400/mo last 30 years? — Simulate a 60/40 portfolio with inflation-adjusted withdrawals to estimate the probability it survives a 30-year retirement.

Load this example

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Initial balance (USD)

Horizon (years)

Assumptions from

Simulations

PortfolioTotal: 100.0%

Lookback start

Lookback end

Method

Cash flow

Inflation (annual %)

Success condition

5,000 randomized paths over 30 years

How the Monte Carlo Simulation works

Each path compounds randomly drawn monthly returns and applies cash flows; thousands of paths build the distribution. Bootstrap methods resample real monthly returns to preserve fat tails better than a normal curve.