Why "Average Returns" Will Mislead Your Retirement Plan

A 7% average return doesn't mean you'll get 7% every year. Here's how sequence of returns risk can wreck a portfolio — and how to stress-test against real history.

---

Most retirement calculators work like this: enter your savings, assume 7% annual returns, see your money last until 95. Clean chart, happy ending.

There's a problem with that math. Markets don't deliver 7% every year. They deliver +30%, then -15%, then +22%, then -40%. The order matters — especially when you're pulling money out.

The Sequence of Returns Problem

Here's a thought experiment. Two retirees, identical portfolios, identical spending. Both experience the exact same market returns over 30 years — just in different order.

Retiree A gets the bad years first. The market drops 40% in their first two years of retirement. They're forced to sell stocks at low prices to cover living expenses. When the market eventually recovers, their portfolio is too depleted to fully benefit.

Retiree B gets the good years first. Strong returns early, then a crash later. By the time the downturn hits, they've built such a cushion that they ride it out easily.

Same average return. Same total market performance. Completely different outcomes.

This is sequence of returns risk, and it's why a simple average-return projection is borderline useless for retirement planning.

What Monte Carlo Simulation Does

Instead of one assumed future, Monte Carlo tests thousands of them.

The basic idea: take decades of actual historical market returns, randomly assemble them into possible 30-year sequences, and run your retirement plan through each one. Some sequences look like the post-war boom. Others look like the 1970s or 2008. Your plan gets stress-tested against all of them.

If 870 out of 1,000 trials end with money left over, you have an 87% success rate. That's not a prediction — it's a survival rate across a wide range of historical conditions.

Why Historical Data Beats Assumptions

retireclarity uses 99 years of S&P 500 and bond returns (1926–2024). That includes:

• The Great Depression
• Post-war economic expansion
• 1970s stagflation
• The dot-com crash
• The 2008 financial crisis
• The COVID crash

Your plan isn't tested against "normal" conditions. It's tested against the full spectrum of what markets have actually done — including the disasters.

One technical note: rather than picking random individual years, the simulation samples blocks of 3-7 consecutive years. This preserves realistic patterns like multi-year bull runs and prolonged recessions. Pure random sampling destroys these patterns; block resampling keeps them intact.

Interpreting Your Success Rate

There's no magic number, but here's a rough guide:

95%+ success rate. Very conservative. You're probably leaving money on the table — retiring later than necessary, spending less than you could, or both. This isn't wrong, but know what you're trading off.

85-95% success rate. Solid ground for most people. You have meaningful margin for error without being excessively cautious.

75-85% success rate. Moderate risk. Not catastrophic, but worth considering adjustments: slightly lower spending, delaying retirement a year, or building in spending flexibility.

Below 75%. The plan has meaningful risk of failure. This doesn't mean you'll run out of money — it means too many historical scenarios end badly. Time to revisit assumptions.

Don't Aim for 100%

A 100% success rate sounds great. It isn't.

It means your plan survives even the worst historical sequences — including ones where you'd have been fine spending more. The person who dies at 92 with $2 million in the bank didn't win retirement planning. They lived below their means for decades.

The goal isn't maximum safety. It's finding the right balance: enough margin to handle bad luck, not so much that you sacrifice experiences you could have afforded.

What Actually Moves the Needle

Things that improve success rates:

• Lower spending relative to your portfolio
• Flexible spending (willingness to cut back in bad years)
• Multiple income sources (Social Security, pensions, part-time work)
• Delaying Social Security (bigger guaranteed income later)
• Roth conversions (reduces tax drag on withdrawals)

Things that hurt:

• Early retirement (longer time horizon means more exposure to sequence risk)
• Fixed high expenses (mortgages, healthcare premiums)
• 100% stocks in early retirement (no buffer when markets drop)
• Large RMDs from traditional accounts (forced selling)

The first five years of retirement are the danger zone. If you hit a bear market right after you stop working, your portfolio takes hits precisely when you're withdrawing.

The Bond Buffer

This is where asset allocation matters most. Holding bonds or cash in early retirement gives you a buffer — money you can spend during downturns without selling stocks at low prices.

The trade-off: bonds have lower expected returns than stocks. Too much in bonds and you sacrifice long-term growth. Too little and you're vulnerable to sequence risk.

retireclarity's Bond Allocation Optimizer tests multiple stock/bond mixes across thousands of historical scenarios to find the balance that works for your situation. It weighs both success rate (survival) and median balance (growth) to recommend an allocation that isn't just safe, but sensible.

What "Failure" Actually Means

A "failed" trial doesn't necessarily mean dying broke. It means running out of money before your target age. But the details matter.

Running out at 94 when you planned to 95 is different from running out at 75. retireclarity's simulation lets you dig into individual trials to see when and how failures happen. A plan that fails only in extreme Depression-era scenarios is very different from one that fails in mild recessions.

Running the Numbers

retireclarity's Chance of Success page runs this simulation automatically using your inputs from the Calculator. You'll see:

• Your overall success rate
• Outcome statistics: median, top 25%, and bottom 25% final balances
• How Roth conversions affect your odds
• Bond allocation optimization to find your ideal stock/bond mix
• The ability to inspect individual trials

The point isn't to find a single "right answer." It's to understand how robust your plan is across a wide range of conditions — and what levers you can pull to improve it.

The Bottom Line

Average returns are useful for back-of-envelope math. They're dangerous for actual retirement planning.

Your plan needs to survive sequence risk: the possibility of a bear market right when you stop earning. Monte Carlo simulation tests that by running your plan through decades of real market history, not hypothetical averages.

If your plan works in the 1930s, the 1970s, 2008, and the good decades, you've got something solid. If it only works when markets cooperate, you've got hope dressed up as a plan.

---

Related Articles

• When to Claim Social Security: The Math Behind the Decision — See how delaying Social Security improves your success rate in tough market scenarios.
• Roth Conversions: When They Make Sense (And When They Don't) — Test whether conversions help or hurt your odds with Monte Carlo simulation.
• The RMD Problem: Why Your IRA Might Cost More in Taxes Than It's Worth — Reducing RMDs can improve success rates by lowering forced withdrawals.

From the Guide: How the Simulation Works · Interpreting Results