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Evidence-first money workflow · Finance & Business

Monte Carlo Retirement Range Simulator

Run a reproducible Monte Carlo retirement simulation with return volatility, inflation-linked withdrawals, survival rate, and percentile balances.

  1. 1Prepare
  2. 2Analyze
  3. 3Review and export

Prepare the evidence

Paste the documented CSV schema or choose a local CSV file. Nothing is sent to Nirmion.

Choose one label for this run. Values are not converted between currencies.

Enter the investable balance at the beginning of year one. Keep account types separate if their taxes or withdrawal rules differ.

Enter the contribution added at the end of each modeled year. Use zero during a pure retirement-withdrawal phase.

Enter the nominal withdrawal in year one. The model increases it by the entered inflation rate in later years.

Use a whole number from 1 through the documented limit. A longer horizon increases assumption uncertainty.

Enter an annual arithmetic return assumption before inflation. It is a scenario input, not a forecast.

Enter the modeled standard deviation of annual returns. Higher volatility widens the simulated range.

This rate increases withdrawals. The tool does not infer inflation from historical data.

Use a whole number from 1 to 10,000. The fixed disclosed seed makes the same inputs reproducible.

Review the analysis

Summary metrics lead back to the rows that support them.

Method and interpretation

How to use Monte Carlo Retirement Range Simulator

Use this Monte Carlo retirement calculator when a single average-return projection hides the effect of return order. It creates many modeled paths from one starting portfolio, contribution, withdrawal, return, volatility, inflation, and time horizon. The result is useful for comparing assumptions, discussing retirement risk, and identifying a plan that needs deeper tax or account-level work. It does not select investments or declare that a retirement plan is safe.

  1. Prepare the input

    Enter the current investable balance, an annual contribution or zero, the first-year withdrawal or zero, and a horizon from 1 to 80 years. Expected return and volatility are nominal annual percentages. Inflation increases only the withdrawal. Choose up to 10,000 trials. Keep all money values in one currency and use assumptions from a documented planning process rather than a best historical period.

  2. Check the worked example

    The worked example starts with USD 500,000, withdraws USD 24,000 in year one, raises that withdrawal by 2.5% annually, and samples returns around 6% with 12% volatility for 30 years. Running 2,000 trials produces the same result every time because Nirmion uses a fixed seed. Change one assumption at a time to understand its effect.

  3. Read the evidence

    Start with the survival rate, then compare the 10th percentile, median, and 90th percentile ending balances. The 10th percentile is a downside scenario boundary inside this model; it does not mean the real plan has exactly a 10% chance of doing worse. The year table shows when the range begins to spread and whether downside paths approach zero well before the final year.

Calculation method

For each year and trial, sampled return = expected return + volatility × seeded standard-normal draw, with a floor of −95%. Ending balance = max(0, opening balance × (1 + sampled return) + contribution − inflation-adjusted withdrawal). Survival means the final balance is above zero. Reported percentiles are sorted trial results at each checkpoint.

Review Portfolio Visualizer’s documented Monte Carlo models and withdrawal methods

Questions this workflow helps answer

Use these questions to confirm that this tool matches the task you need to complete.

  • What range of retirement portfolio outcomes does a Monte Carlo simulation show?
  • How do volatility and inflation-linked withdrawals change retirement portfolio survival?
  • What do 10th, 50th, and 90th percentile retirement balances mean?

Limits and decision boundary

The model assumes independent normally distributed annual returns and end-of-year cash flows. Real returns can have fat tails, serial correlation, changing asset allocation, fees, taxes, required distributions, and different inflation behavior. A fixed seed improves auditability but does not make a sample representative of future markets. Use professional planning for decisions that depend on tax law, pension choices, or account withdrawal order.

Common mistake

Do not treat the median path as the expected real-life outcome or optimize until one scenario reaches a preferred success percentage. Test conservative return, volatility, inflation, spending, and horizon assumptions, and inspect downside balances as well as the headline rate.

Your pasted values and selected CSV files are processed in this browser tab. This workflow does not connect to a bank, save a budget, or provide financial, tax, legal, or investment advice.

Questions about this workflow

Is the survival rate a guarantee?

No. It is the share of entered-model trials ending above zero. Real market behavior, taxes, fees, cash-flow timing, and decisions can differ.

Why are results reproducible?

The calculator uses a fixed pseudo-random seed so the same inputs produce the same audit result. Change an input to compare scenarios.

Can I enter a contribution and withdrawal together?

Yes. The annual net cash flow applies both, although most users should split accumulation and retirement phases when those amounts change materially.

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