Monte Carlo: portfolio survival
Run 10,000 paths through your portfolio. Accumulation mode shows where you might land; withdrawal mode shows the FIRE survival probability. Sequence-of-returns risk made visible.
A Monte Carlo simulator runs the same portfolio thousands of times with independently random returns and asks: what's the spread of where I might land? A single PAC backtest gives you one path; this gives you the whole envelope.
Two modes:
- Accumulation — start with capital, contribute monthly, see where you might land in N years. The fan chart shows the spread (10th to 90th percentile) of outcomes.
- Withdrawal (FIRE) — start with capital, spend monthly, see how often the portfolio survives. This is the classic Trinity-study question, generalized to any portfolio mix and any spending level.
For one calibrated walk through the same math, see the PAC backtest. For a quick FIRE-number calculator without the probability lens, see the FIRE calculator.
How big could my pile get in N years if I keep contributing? The fan chart below shows the spread of outcomes across thousands of simulated paths.
60/40 Classic
Methodology: each path independently draws monthly returns from a lognormal distribution calibrated to each asset's documented annualized return and volatility. Mixed portfolios sum weighted asset returns at zero correlation (a simplification — real correlations would slightly tighten outcome dispersion). The model captures distributional risk well; it does not capture fat tails, regime change, or covariance shifts.
How to read the fan chart
The dark line in the middle is the median path — half the simulations end above it, half below. The bands around it widen as time goes on, because uncertainty compounds. The outer band edges are the 10th and 90th percentile: 80% of all simulated paths land between those two lines at any given point in time. The inner band (25th-75th) contains 50% of paths.
A wide fan with high median means high expected return but high variability. A narrow fan with low median means smooth ride, modest result. There is no perfect answer — the tradeoff is what investing is.
Sequence-of-returns risk, in one chart
In withdrawal mode, the survival probability is the share of simulated paths that end with a positive balance. If 90% of paths survive, you're probably fine. If 60%, you're rolling the dice. The risk that wrecks 30% of those paths isn't bad average returns — it's bad timing of returns. Two paths with identical 30-year returns can have wildly different outcomes if one has its bear market in years 1-3 and the other in years 27-30. The tool captures this directly: early losses with constant withdrawals are catastrophic in a way that late losses are not.
What the model does and doesn't do
What it does:
- Captures expected return, volatility, and the basic dispersion of outcomes.
- Captures sequence-of-returns risk in withdrawal mode (different paths have different timing).
- Captures the cost of TER drag over long horizons.
- Lets you compare 10 ETFs and 6 portfolio strategies on the same axis.
What it doesn't do:
- Doesn't model fat tails — 2008-style crashes happen more often in reality than a lognormal model says they should.
- Doesn't model correlation between assets — a real 60/40 portfolio has tighter dispersion than this tool will show, because stocks and bonds aren't perfectly independent.
- Doesn't model regime change — interest rates, expected returns, and volatility have all changed over decades.
- Doesn't model your behavior — the real reason most investors underperform isn't the math, it's selling at the bottom.