Two retirees with identical portfolios, identical withdrawal rates, and identical 30-year average returns can end up in completely different financial situations. One ends with $2 million still in the account. The other runs out at 82.
The difference is the order in which their good and bad years happened.
I show this to clients with a thought experiment. Imagine two $1M portfolios, each pulling 4% per year for inflation, both averaging 7% over 30 years. Portfolio A has its three worst years (say −30%, −20%, −15%) in years 1–3. Portfolio B has the same three years in years 28–30. Same average return. Same withdrawal rate. Same time horizon.
Portfolio A runs out around year 22. Portfolio B finishes with $2.5M.
This isn’t a hypothetical. The 1929 retiree, the 1973 retiree, and the 2000 retiree all faced bad-years-early sequences. Each was forced to sell into a falling market to fund withdrawals, locking in losses that compounding never recovered. Average-return models said they should have been fine. Sequence reality said otherwise.
Why early bad years hurt so much more than late bad years
The math comes down to dollar-cost averaging in reverse. When you’re withdrawing, a −30% year early means you’re selling more shares to fund the same withdrawal — and those shares are gone before they can recover. A −30% year late hits a portfolio that’s already largely depleted, so the dollar damage is smaller. The same percentage decline does very different damage depending on when it lands.
This is why a single Monte Carlo run that says “your retirement works at 7% average return” can be deeply misleading. The retiree who experiences the average outcome is rare. The retiree who experiences the bottom-quartile sequence early might fail in 15 years even when the average says 35.
What this calculator does
Standard Monte Carlo runs 10,000 random sequences and reports the success rate. This tool goes one step further: it splits the results by what happened in the first decade.
You’ll see four success rates instead of one:
- Best-quartile first-decade returns — what happens if the early years are kind
- Above-average first-decade returns — the typical good case
- Below-average first-decade returns — the typical bad case
- Worst-quartile first-decade returns — what happens if you retire into a 1929/1973/2000-style window
The split between best and worst is often dramatic. A plan that looks like a solid 88% success rate overall might be 99% success in good early sequences and 50% in bad ones. The single-number average masks the conditional risk.
What to do with the result
Three concrete adjustments that make a sequence-vulnerable plan more robust:
- Hold a 2–3 year cash bucket. When markets drop early, you withdraw from cash instead of selling depressed stocks. This breaks the sell-the-bottom dynamic. The cost is the foregone return on those dollars, which is typically less than the cost of a forced bad-year withdrawal.
- Build flexibility into the withdrawal rate. A plan that says “I’ll withdraw 4% no matter what” is more fragile than “I’ll withdraw 4% in normal years and 3% after a −15% year.” Even small adjustments break the cycle.
- Consider a rising-equity glide path. Counterintuitively, holding more bonds at the start of retirement (and more stocks later) outperforms a static allocation in many sequence scenarios. It’s one of the more interesting findings in modern retirement research.
A word of honesty: no calculator eliminates sequence-of- returns risk. The tool makes it visible. Living with it requires a plan that has slack built in — not optimization to the last basis point.
For $500K+ households, this is where coordinated planning earns its keep: building withdrawal flexibility, holding the right cash buffer, and adjusting allocation in response to early markets rather than to a fixed schedule.
Run yours.