Monte Carlo Simulation

Overview

A single projection draws one tidy line. Real markets don't move in tidy lines. The Monte Carlo simulation runs your retirement plan through many possible return paths and shows the range of outcomes, so you can see how your plan holds up when returns come in better or worse than expected.

Available on: Premium. On Pro, the section shows a locked preview and runs nothing.

What You See

• Success probability: the share of simulated paths where the money never runs out before your longevity age.
• Simulated balance by age: a fan chart. The middle line is the median path. The shaded band runs from the 10th to the 90th percentile, so eight in ten simulated paths land inside it.
• Paths not depleted, by age: how the success share changes as the years go on.
• Median depletion age: among the paths that do run out, the typical age they run out at. If no path runs out, the section says so.
• A footer such as 1000 simulations · seed 4815162342, and the return model used.

How It Works

Each simulated year draws a random return around your expected return, spread out by your return volatility assumption (15% by default). The model is parametric lognormal, which keeps a year's loss above −100%. Every path then runs through the same plan as the main projection: contributions until retirement, then spending, income sources, and your withdrawal strategy.

The number of paths comes from the Monte Carlo paths assumption: 1,000 by default, from 100 to 5,000.

Same inputs, same result

The simulation is seeded. By default the seed comes from your account, your assumptions, and the date of your inputs, so opening the plan again on the same day with the same numbers shows exactly the same fan. Change an assumption and you get a fresh run.

Tap Run again to try a new random seed. The footer shows the seed each time, which makes a run easy to tell apart from the last one.

Frequently Asked Questions

What is a good success probability?

That depends on how flexible your plans are. The figure only tells you how often the plan held up across the simulated paths, under your assumptions.

Why did my result change?

Your inputs changed, an assumption changed, or you tapped Run again. With the same inputs, the same seed, and the same date, the result is identical.

Does a volatility of 0% do anything?

With no volatility every path is the same, so the simulation matches the main projection exactly.

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