This article is a case study in using our Monte Carlo calculator to see sequence-of-returns risk inside one plan. Sequence risk is the rule that once withdrawals start, the order of market returns matters as much as their average, because shares sold during early losses never participate in the recovery. We built a single 65-year-old retiree with $1 million in the calculator and ran the plan two ways. Projected in a straight line, with every year earning its average return, the plan reaches age 95 with about $1.9 million, nearly double what it started with. Replayed through 5,000 Monte Carlo simulations, with the same average assumptions arriving in random order, the plan still runs dry before 95 in 12 runs out of 100. The straight line assumes one sequence, the average every year. The simulation prices the orderings it skips.
Why the order matters once withdrawals start
While you are saving, order is irrelevant. A loss in year one and a gain in year twenty produce the same ending balance in either order, because nothing leaves the account. Withdrawals break the symmetry. Money sold in a down year to fund spending is gone before the rebound arrives, so an early loss compounds against every remaining year of the plan. A retirement can earn a healthy average return and still fail if the worst years land first.
The plan we built
We kept the inputs minimal so the effect has nowhere to hide. The retiree is single, 65, retiring this year, and planning to age 95. The savings are one account, a traditional 401(k) holding $1 million in a stock fund growing at 7% a year. Spending is $4,500 a month in today's dollars. Social Security pays $2,500 a month starting at 67, entered with the Manual toggle on the Profile tab. The engine inflates spending and the benefit at 2.5% a year, reads 12% annual volatility from the stock-fund label, and grosses every 401(k) withdrawal up for federal income tax. The portfolio carries the full $4,500 for the first two years, then only the gap above the check.
The straight-line projection says you're fine
Most retirement calculators project a plan the way a spreadsheet does. Pick a return, compound every year at exactly that number, and read the ending balance. Our engine can run that projection too, compounding the stock fund at a constant 6.3% a year and a 4.5% bond fund at 4.3%, the geometric averages of the same assumptions the simulation draws from.
| Balance at age | 100% stocks | $200,000 in bonds | $400,000 in bonds |
|---|---|---|---|
| 75 | $1,309,000 | $1,258,000 | $1,207,000 |
| 85 | $1,668,000 | $1,532,000 | $1,397,000 |
| 95 | $1,927,000 | $1,673,000 | $1,421,000 |
Every allocation not only survives but grows. With Social Security covering most of the budget, the portfolio earns more than it gives up, so the balance climbs the whole way and reaches 95 worth more than it started. Moving $400,000 into bonds shows up as a $506,000 cost at 95 with nothing gained. Both conclusions rest on the same hidden assumption. A straight line is a sequence with no bad years in it, and no retirement gets that sequence.
The same plan, 5,000 sequences
The Monte Carlo tab replays the identical plan against 5,000 random orderings of the same return assumptions and draws the result as a fan chart. Every path starts from the same $1 million.
The straight line never touched zero. In the simulation, 12 sequences in 100 did. The 90th percentile retirement compounds past $4 million; the median finishes near $1.4 million. The 10th percentile retirement loses ground in the first few years, sells into weakness for the rest of the plan, and runs dry around age 90. Neither retiree did anything differently.
The raw simulation paths show how early the two fates separate. Sorted by balance at the five-year mark, runs in the worst quarter went on to fail about a third of the time, while runs in the best quarter almost never failed, roughly one time in a hundred. The failing runs held a median $788,000 at year five against $1.15 million for the survivors.
What a bond allocation buys
You cannot choose the decade you retire into. You can choose how hard the portfolio rides it. We moved $200,000, then $400,000, of the 401(k) into the bond fund and changed nothing else between runs.
| Allocation | Success rate | Broke by age 90 | Median balance at 95 | Best-tenth balance at 95 |
|---|---|---|---|---|
| 100% stocks | 88% | 6% | $1,400,000 | $4,250,000 |
| $200,000 in bonds | 91% | 2% | $1,260,000 | $3,610,000 |
| $400,000 in bonds | 93% | 1% | $1,110,000 | $2,830,000 |
Here the bonds help on both fronts. The success rate climbs from 88% to 93%, and the odds of being broke by 90 fall from 6% to 1%, because lower volatility protects the weak sequences more than the lower return costs the plan. The bill lands on the best-tenth outcomes, which give up roughly $1.4 million of upside at 95. The straight line priced the same move as pure loss. The simulation shows what the money buys. Bonds in this plan work like insurance, capping what a bad early sequence can do at a premium paid out of the best markets.
Run it on your own numbers
The whole comparison takes a few minutes in the calculator, free and with no login.
- On the Profile tab, enter your age, retirement age, and monthly retirement spending, then switch the Social Security card to Manual and type the figure from your ssa.gov statement.
- On the Assets tab, enter your accounts. The engine reads volatility from each account's name, so stock funds get 12%, bond funds 6%, and cash 0.5%, or you can pick an investment objective to set an exact stock-bond mix.
- On the Monte Carlo tab, run 1,000 simulations and look at the fan chart's spread, not just the headline rate. Then move money between a stock account and a bond account and run again. Rates are stochastic, so expect to land within a point or two of the numbers above on identical inputs.
The bottom line
Sequence-of-returns risk is the distance between the two answers in this article. A straight line compounds one assumed sequence and reports that the plan works, with about $1.9 million left at 95. A Monte Carlo simulation replays the same plan against thousands of sequences and reports how many survive, 88 in 100 here. Only the second answer prices the order. Our guide to what counts as a good success rate covers how to read and act on that number.
Sources
- William P. Bengen, "Determining Withdrawal Rates Using Historical Data," Journal of Financial Planning, 1994.
- Philip L. Cooley, Carl M. Hubbard, and Daniel T. Walz, "Retirement Savings: Choosing a Withdrawal Rate That Is Sustainable," AAII Journal, 1998 (the Trinity study).
- RetirFi simulation methodology, described on our about page. Scenario figures come from the same engine that runs the calculator.
Test your plan against the bad-years-first scenario.
RetirFi reshuffles your returns across thousands of orderings, so you can see how sequence of returns risk hits your timeline and which adjustments protect you.
Open the Calculator →