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Retirement Monte Carlo Simulator

Stress-test your retirement plan against hundreds of simulated market histories. Instead of assuming one smooth average return, the simulator draws a different random sequence of good and bad years for every path and reports how often your pot survives the full horizon.

New to safe withdrawal rates? Read the 4% rule guide

Share this result set

Every input you change updates the URL. Copy the link to send your exact scenario to a partner, accountant or friend.

Your numbers

£1,000,000
£

Your invested pot on day one of retirement.

£40,000
£

A fixed real (inflation-adjusted) amount taken at the start of every year.

30 yrs
yrs
5.0%
%

After inflation. Long-run global equities have historically averaged roughly 5% real; that is history, not a promise.

12%
%

Equity-heavy portfolios have historically sat around 10-18% annual volatility; bond-heavy mixes lower. Illustrative, not a forecast.

More paths smooth the percentile bands; the story rarely changes.

Same inputs, same simulation: identical settings always reproduce exactly the same paths, so your results are stable across reloads and shares. Re-roll draws a fresh set of random market histories.

What happens to my data?

All calculations run in your browser. Nothing is sent to our servers. Copy the link to share.

Success rate

85.6%

Median ending balance

£1,047,823

10th percentile ending

£0

Worst decile runs dry by

Year 27

Across 1,000 simulated retirements, 144 ran out of money before year 30. The unluckiest 10% of paths had already failed by year 27. Figures are illustrative, not financial advice.

Balance fan chart

The spread of outcomes across every simulated path, year by year. Half of all paths end inside the dark band.

10th to 90th percentile 25th to 75th percentile Median
£0£1.9m£3.9m051015202530
Year10th percentileMedian90th percentile
10£539,920£1,011,993£1,798,623
20£245,594£1,080,299£2,488,990
30£0£1,047,823£3,879,269

The average return is not the story. The order of returns is.

Two retirees can earn identical average returns and end up in completely different places, because the one who hits a crash in the first five years is selling cheap units to fund withdrawals that never get the chance to recover. That is sequence of returns risk, and it is exactly the spread this fan chart makes visible: every path here has the same expected return, and they still fan out into fortunes and failures. Our sequence of returns risk article walks through why the first decade of retirement carries most of the danger, and the 4% rule guide covers where the classic withdrawal rate came from and where it creaks.

What Monte Carlo does and does not do

This simulator draws each year's return independently from a normal distribution (i.i.d. normal real returns). Real markets are messier: crashes are more frequent and more violent than a normal distribution allows (fat tails), bad years cluster together, and returns partly depend on the valuations you start from. It also ignores fees, taxes, state or Social Security pensions, and the entirely human response of spending less in a crash. Treat the output as a stress test of a rigid plan, not a prediction. It is illustrative and it is not financial advice.

How the simulation works

Each simulated retirement starts with your pot, takes the full withdrawal off the balance at the start of every year, then applies one random real return drawn from a normal distribution with your chosen mean and volatility. If the balance cannot fund a withdrawal, that path has failed and stays at zero for the rest of the horizon.

The success rate is simply the share of paths that funded every withdrawal. The fan chart sorts every path's balance at every year and plots the 10th, 25th, 50th, 75th and 90th percentiles, so you can see the whole distribution rather than one trajectory.

Everything runs on a seeded random number generator, which is why the same inputs always produce the same simulation. The re-roll button steps the seed to draw a fresh set of market histories; if the success rate swings noticeably between rolls, increase the number of simulations.

Frequently asked questions

What does the success rate actually mean?
It is the share of simulated retirements that funded every single withdrawal to the end of your horizon. A 90% success rate means that in 9 out of 10 simulated market histories the pot never ran dry. It is not a probability of your future, because the simulation is a simplified model of markets, but it is a useful way to compare plans: a plan that fails in 30% of simulations is clearly more fragile than one that fails in 5%.
What return and volatility should I use?
The inputs are real (after-inflation) figures. Long-run global equity returns have historically averaged roughly 5% real with annual volatility somewhere around 10-18%, while bond-heavy portfolios sit lower on both. Those are historical observations, not guarantees, and reasonable people use more conservative numbers. If you want the classic 4% rule setup, the preset uses a 5% real return and 12% volatility on a 30-year horizon.
Why do I get exactly the same result every time?
By design. The simulator uses a seeded random number generator, so the same inputs always reproduce the same set of simulated paths. That keeps results stable across page reloads and shared links, and makes changes honest: when you nudge the withdrawal and the success rate moves, it is your input that moved it, not fresh random luck. The re-roll button steps the seed to draw a genuinely new set of market histories.
What does Monte Carlo simulation miss?
This model draws each year independently from a normal distribution, and real markets do not behave that politely. Crashes are bigger and more common than a normal distribution predicts, bad years cluster into bear markets, and future returns partly depend on starting valuations. The model also ignores fees, taxes, state pensions and the fact that real retirees cut spending in bad years. Treat the output as a stress test, not a forecast.
How does this relate to the 4% rule?
The 4% rule says a retiree withdrawing 4% of the starting pot, adjusted for inflation each year, historically survived 30 years in almost every US market period studied. This simulator generalises that test: instead of replaying history, it generates hundreds of random market histories from your return and volatility assumptions and counts how many the plan survives. The default inputs (a 40,000 withdrawal from a 1,000,000 pot over 30 years) are the 4% rule setup.
Do I need a 95% or 100% success rate?
Not necessarily. Chasing 100% success against a pessimistic model usually means working years longer to insure against scenarios you could handle by trimming spending for a while. Many planners consider 80-90% acceptable when spending is flexible, because the failure paths mostly assume a retiree who robotically withdraws the same amount through a decade-long slump. The success rate is a fragility gauge, not a pass or fail exam.

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