Monte Carlo Simulation

Most retirement calculators show you one line: your portfolio grows at 7% per year, you withdraw steadily, and the balance either lasts or it doesn't. That single line is a useful approximation – and a deeply misleading one.

Real markets don't return 7% every year. They return +28% one year, −18% the next, +14% after that. The sequence, the volatility, and the randomness all matter. A single projected line hides all of that.

Monte Carlo simulation solves this by running thousands of scenarios simultaneously – each with a different randomized sequence of returns drawn from historical distributions. Instead of one outcome, you get a range:

"Probability of success" means the portfolio doesn't reach zero before the end of the horizon. An 85% success rate means that in 850 out of 1,000 simulated retirements, the money lasted.

What the Simulation Actually Does

Each Monte Carlo run samples returns randomly from a distribution based on historical data – mean return, standard deviation, and correlation between asset classes. Run it 10,000 times and you get 10,000 different retirement paths.

The output isn't a prediction. It's a probability distribution of outcomes – showing not just the most likely result but the range of possibilities and how likely each is.

• The median line shows the middle outcome – half of simulations did better, half did worse;
• The 10th percentile line shows what a bad but not catastrophic sequence looks like;
• The 5th percentile line shows near-worst-case scenarios – useful for stress testing;
• The width of the cone reflects how much uncertainty compounds over time – wider cones mean more uncertainty, not worse expected outcomes.