Monte Carlo simulation for retirement planning, explained

Most retirement projections give you one number: “your pot will be worth £640,000 at 67.” That number comes from assuming the same growth rate every single year. Markets do not behave like that. A Monte Carlo simulation replaces the single straight line with thousands of possible futures, so you can see the range of outcomes rather than one optimistic guess.

What a Monte Carlo simulation actually does

The method is simple to describe. Take your starting portfolio, your planned contributions and your planned withdrawals. Then simulate the journey year by year, drawing each year’s investment return at random from a distribution based on how each asset class has behaved historically: its average return, how much it swings (volatility), and how it tends to move relative to other assets (correlation).

Do that once and you have one possible future. Do it a thousand times and you have a thousand. Some contain an early crash, some a long bull market, most something in between. Together they form a distribution of outcomes.

How to read the results

• Probability of success: the share of simulated futures in which your money lasts as long as you need it to. If 820 of 1,000 paths fund your plan, that is an 82% success probability.
• The median path: the middle outcome. Half of the simulated futures end above it and half below.
• The percentile range: often shown as a fan chart. The 10th percentile is a poor-markets outcome, the 90th a strong-markets one. The width of the fan is your uncertainty.

A success probability is not a forecast. It tells you how robust a plan is under the model’s assumptions. A plan at 60% is fragile. A plan at 99% may mean you are saving more or spending less than you need to.

Why a single growth rate misleads

Two portfolios can share the same average return and produce very different retirements, because the order of returns matters once you are withdrawing money. A fall in the first few years of retirement does more damage than the same fall twenty years in. A fixed-rate projection cannot show this. A simulation can.

The limits you should know about

• The output is only as good as the assumptions. Return and volatility figures drawn from history may not repeat.
• Many models assume returns follow a normal distribution, which understates how often extreme events happen. Pairing a simulation with historical stress tests helps cover that gap.
• Simulations usually ignore your personal tax position and assume you follow the plan without changing behaviour. Real people adjust spending when markets fall.

Using the results to make decisions

The value of a simulation is in comparing options. Rerun the plan retiring two years later, or contributing £100 more a month, or holding more bonds, and see how the probability of success shifts. The lever that moves the number most is usually where your attention should go.

This article is general information, not financial advice. Projections are illustrative and capital is at risk.