Investing & WealthAdvanced

Monte Carlo Investment Simulator

Inputs

Results

Enter values and calculate to see results.

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Disclaimer: Probabilistic modelling and withdrawal rate simulations represent statistical mathematical scenarios based on historical parameters, not guaranteed future financial outcomes. Market volatility, inflation and sequencing risk can cause actual portfolio longevity to differ significantly. Consult an FCA-regulated financial adviser.

Modelling a range of outcomes instead of one

A single average return hides the range. Simulating many volatile paths shows the spread of outcomes, and the spread is usually much wider than people expect.

What this calculator does

  • Simulates many possible investment paths using a mean return and a volatility assumption.
  • Reports the median outcome and the 10th, 25th, 75th and 90th percentiles.
  • Estimates the probability of reaching a target and of running out entirely.
  • Replaces a single point projection with a distribution.

How the calculation works

Instead of applying one return every year, the simulation draws a different random return for each year of each path, from a distribution defined by the mean return and volatility you enter. Running a thousand such paths produces a thousand different endings, and the useful information is in their spread rather than in any single one. The median is the middle outcome — half of the paths did better, half worse — and it sits below the mean because a few very good paths pull the average up without being typical. The percentiles describe the range: the 10th is a poor but entirely plausible outcome, the 90th a good one. The probability of ruin counts the paths that hit zero, which is the number that matters most when withdrawals are being taken. Presenting a distribution rather than a point estimate is the whole purpose, because a single projection implies a precision that volatile markets do not offer.

The rule

For each of many paths, and each year: value = (value + contribution − withdrawal) × (1 + a return drawn at random from a distribution with the given mean and volatility). The endings are then sorted into percentiles.

Step by step

  1. Draw a random annual return from the distribution defined by the mean and volatility.
  2. Apply contributions or withdrawals for the year, then the return.
  3. Repeat for every year of the horizon to complete one path.
  4. Repeat for the number of simulated paths requested.
  5. Sort the outcomes and report the median, the percentiles, and how many paths reached the target or hit zero.

Worked example

£100,000 invested with £12,000 added each year for twenty years, assuming a 7% mean return with 15% volatility, against a £1,000,000 target, over a thousand simulated paths.

What was entered

Inputs used in the worked example
Initial investment£100,000
Annual contribution / savings£12,000
Annual retirement spending£0
Expected mean return7% a year
Annual volatility15%
Simulation timeframe20 years
Number of simulated paths1,000
Target wealth goal£1,000,000

The arithmetic

  1. The median outcome is about £779,979 — half the paths finished above this and half below.
  2. The 10th percentile is about £415,590 and the 90th about £1,529,945, a spread of more than a million pounds on identical inputs.
  3. Only 33.1% of paths reached the £1,000,000 target, despite the mean return of 7% suggesting it should be close.
  4. No path ran out of money, because contributions are being added and nothing is withdrawn.
  5. The mean outcome of about £908,349 is well above the median, because a minority of very strong paths pull the average up.
  6. The gap between the mean and the median is exactly why a single average-return projection misleads.

What the calculator returns

Results produced by the worked example
Median outcome£779,978.56
10th percentile£415,589.99
90th percentile£1,529,945.06
Chance of reaching the target33.1%
Chance of running out0%
Mean outcome£908,349.49

Key assumptions

  • Annual returns are drawn independently from a distribution defined by the mean and volatility you enter.
  • Contributions and withdrawals happen once a year.
  • The simulation is reproducible, so the same inputs always produce the same distribution.

Limitations

  • The model assumes returns are independent from year to year and follow a well-behaved distribution. Real markets show crashes, recoveries and correlations that such a model understates, so the true tails are usually fatter than the simulation suggests.
  • Everything depends on the mean and volatility you supply. Those are assumptions, not knowledge, and the output inherits all their uncertainty.
  • Inflation is not applied unless the mean return you entered is a real return.
  • Tax and charges are not modelled, and both reduce every path.
  • A probability from a simulation is a property of the model, not a fact about the future.
  • This is a projection, not advice.

Common questions

Why is the median lower than the mean?
Because the distribution of outcomes is skewed. A small number of exceptionally strong paths pull the average up without being typical, so the median — the middle outcome — is the more representative figure to plan around.
Why did only a third of paths reach the target when the mean return was 7%?
Because volatility drags on compounded growth. A sequence of returns averaging 7% ends up below what a steady 7% would produce, and only the better paths clear the target. This is precisely the gap a single-rate projection hides.
Does a 0% chance of ruin mean it is safe?
No. Nothing is being withdrawn here and contributions are being added every year, so no path can reach zero. The ruin probability only becomes meaningful once withdrawals are being taken.
Can I rely on these probabilities?
They describe the model, not the future. The assumptions about mean return and volatility drive everything, and real markets behave less politely than the distribution assumes, so extreme outcomes are more likely in reality than the simulation implies.

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Official sources

Every figure in this guide was checked against the sources below. Where a source could not confirm a figure, it is marked as requiring verification rather than presented as settled.