Simulating a Portfolio's Future
How simulation turns one history into thousands of possible futures, what the resulting ranges look like for shares, bonds, and a 60/40 mix, and why the percentages a planning tool reports deserve less trust than they seem to.
The short version
History happened once. A simulation reshuffles it to produce thousands of paths that could have happened, and reports the spread. Run 10,000 times on 98 years of US returns, $10,000 left in shares for 30 years ended anywhere from about $32,000 to about $925,000 in the middle nine tenths of cases. A 60/40 mix had a lower typical result and a better bad one. The method is useful because it replaces a single projected number with a range and puts the poor outcomes in view. Its percentages are only as good as its assumptions: that the future is drawn from the past, that each year is independent of the last, and that the investor never sells.
By the end of this lesson, you'll be able to
- Explain how a simulation built from historical returns works
- Read a table of simulated outcomes, including what a percentile means
- Identify the assumptions behind a simulation and explain why its probabilities are rough
Why this matters
Some retirement calculators and planning tools report a figure like "an 87% chance of success". A figure like that comes from a simulation. The method is a real improvement on projecting a single average return, and it's easy to mistake for a forecast. This lesson builds one from scratch, so you can see exactly what goes in and how far to trust what comes out.
From one history to many
The record from 1928 through 2025 is one sequence of 98 years. It contains the crash of 1929 to 1932 at the start and a long rise at the end. A different order of the same years would have given investors very different experiences, as Sequence Risk explains.
A simulation makes use of that. The version here works like this.
- Pick one year at random from the 98. Use the returns shares and bonds really had in that year.
- Do that 30 times to make one possible 30-year path, and apply it to a portfolio.
- Repeat 10,000 times, and sort the 10,000 ending values.
The same year can be picked more than once in a path, and shares and bonds always take their returns from the same year, so the way they moved together is kept. This kind of simulation, which draws from actual history, is often called a bootstrap. The more general name for the approach is a Monte Carlo simulation. A way of exploring an uncertain outcome by generating thousands of random possible paths and looking at the spread of results. Its answers depend on the assumptions used to generate the paths. Glossary.
What it shows: a single sum
| Outcome | All shares | 60% shares, 40% bonds | All bonds |
|---|---|---|---|
| Poor: only 1 path in 20 was worse | $31,730 | $37,440 | $19,712 |
| Below typical: 1 path in 4 was worse | $90,031 | $71,866 | $28,513 |
| Typical: half were better, half worse | $181,276 | $111,794 | $37,516 |
| Above typical: 1 path in 4 was better | $356,184 | $170,401 | $49,085 |
| Excellent: only 1 path in 20 was better | $925,043 | $298,412 | $73,449 |
Built from Aswath Damodaran's yearly returns for the S&P 500 and 10-year Treasury bonds, rebalanced yearly, before fees, taxes, and inflation.1 These are illustrations of a method, not forecasts.
Each row is a percentile. The first row is the 5th: in 5% of the paths, the result was lower than that. The middle row is the median.
- The range is enormous. For shares, the excellent outcome is 29 times the poor one. A projection that says "$10,000 grows to $181,000" is quoting the middle of that range as if it were the whole of it.
- Shares had the best typical result by a wide margin. Path by path, they ended ahead of the 60/40 mix about 85% of the time.
- The mix did better when things went badly. Its poor outcome was $37,440, against $31,730 for shares. That's what the bonds are for: they cost a great deal in the typical case and help in the worst ones.
- Bonds alone were the worst choice in every row, including the poor one. Over 30 years, the low return did more damage than the low volatility prevented.
The rest of this lesson is for members
Still to come in this lesson: A shorter period, Saving regularly, What the simulation assumes, Using a simulation well, the key takeaways, and 2 quiz questions with explanations.
Membership opens every lesson in the curriculum, the capstone projects, the interactive tools, and the members-only channels in the Hyperion Entities Discord. The first lesson of every module stays free.
Go deeper
- What These Models MissPortfolio Theory and Risk (depth track)
- Expected Return and Standard DeviationPortfolio Theory and Risk (depth track)
- Sequence RiskPart 5: Building a Portfolio
- CompoundingPart 1: Foundations
Notes and sources
- Aswath Damodaran, NYU Stern School of Business. Historical Returns on Stocks, Bonds and Bills, with annual data through 2025 (updated January 2026). Checked 2026-10-12. Back to text