Sequence of Returns Risk: Why Your Retirement Year Matters More Than Your Average Return

Two Retirees, Nearly the Same Average, Opposite Outcomes

Imagine two retirees, each starting with a $1,000,000 portfolio invested in U.S. stocks. Both withdraw 4% in the first year ($40,000) and adjust that amount upward each year for inflation. Both experience roughly the same long-run market performance: the retiree who started in 1966 saw a 30-year nominal compound annual growth rate (CAGR) of about 10.6%, while the one who started in 1982 saw about 10.9%.

Those numbers are remarkably close. You might expect similar outcomes. But you would be wrong.

The 1966 retiree ran out of money before reaching 30 years. The 1982 retiree finished with roughly $14.1 million in nominal terms. Same withdrawal rule, similar long-run returns, completely different retirement experiences. The difference was not the average return. It was the sequence in which those returns arrived.

This is sequence-of-returns risk, and it is arguably the single greatest threat to a retirement portfolio that relies on withdrawals. It is also one of the most underappreciated concepts in personal finance.

Note: The examples in this guide use S&P 500 total return data for illustration, since it is the most widely studied dataset in retirement research. A globally diversified portfolio (such as a mix of U.S. and international stocks, similar to a total world fund) would show similar sequence-of-returns dynamics. The phenomenon is not unique to U.S. markets.

What Is Sequence of Returns Risk?

Sequence-of-returns risk (often shortened to "sequence risk") is the risk that the timing and order of investment returns will harm your portfolio when you are making withdrawals. It exists because withdrawals interact with returns in a way that accumulation does not.

During accumulation (when you are saving and investing), the order of returns does not matter. A portfolio that earns +20%, -10%, +15% over three years ends at the same balance as one that earns -10%, +15%, +20%, assuming no contributions or withdrawals. This is basic compound math.

But once you begin withdrawing money, that symmetry breaks. Here is a simplified example to see why:

Consider a $1,000,000 portfolio that earns -30% in year one, then +30% in year two, with a $50,000 annual withdrawal taken at the start of each year:

Now reverse the sequence. Same two returns (+30%, then -30%), same withdrawals:

Same average return, same total withdrawal. But getting the bad year first leaves you $30,000 poorer. Over 30 years, this effect compounds dramatically. The early returns anchor everything that follows, because withdrawals during a downturn permanently reduce the capital base that future gains compound on.

This is the core mechanism. But sequence risk is not just about stock market crashes. As financial planner William Bengen showed in his landmark 1994 research, the most damaging sequences combine weak real equity returns with high inflation. When your portfolio is flat or falling and your withdrawals are growing with inflation, the damage compounds from both directions.

1966 vs. 1982: A Year-by-Year Comparison

Let us return to our two retirees and look more closely at what actually happened. The raw 30-year CAGR numbers were similar, but the first decade told two completely different stories.

The first 10 years: where the outcome was decided

The 1966 retiree's first decade delivered an annualized real return (after inflation) of roughly -2.1%. That is a decade of going backward in purchasing-power terms. Meanwhile, the 1982 retiree's first decade produced an annualized real return of roughly +12.8%.

Let that contrast sink in. One retiree watched their portfolio lose real value for an entire decade while making inflation-adjusted withdrawals. The other saw their portfolio nearly triple in real terms, building an enormous cushion that would carry them through any future downturn.

The 1973-1974 inflationary bear market

The damage to the 1966 cohort centers on the 1973-1974 period. The S&P 500 fell roughly 14% in 1973 and another 26% in 1974, while the Consumer Price Index rose 6.2% and then 11.0% in those same years. This combination was devastating for retirees: portfolio values dropped sharply while inflation-adjusted withdrawals increased.

Bengen's research identified this as the most destructive event in the historical record. He noted that the damage from 1973-1974 "reaches back" to retirees who started 20 or more years earlier, because the combined effect of falling asset values and rising inflation erodes purchasing power from both sides simultaneously. For the 1966 retiree, this event arrived during years 7 and 8 of retirement, when the portfolio had already been weakened by mediocre returns and steady withdrawals.

A supporting case: the 1969 retiree

To reinforce that averages can mislead, consider the 1969 starting year. The 1969 retiree actually had a higher 30-year nominal CAGR than the 1966 retiree. On paper, they look like the safer bet. But the 1969 cohort also depleted their portfolio under the same 4% inflation-adjusted withdrawal rule, because the 1973-1974 bear market hit even earlier in their retirement (years 4 and 5), when withdrawals had barely begun to compound.

This is why "average return" is the wrong summary statistic for retirement planning. Two portfolios with the same, or even better, long-run averages can have opposite outcomes depending on what happens in the critical early years.

Every Starting Year: The Full Picture

The 1966 and 1982 examples are powerful, but they are just two data points. To really understand sequence risk, you need to see the pattern across every possible starting year. The heatmap below shows the portfolio balance at each year of a 30-year retirement for every starting year from 1950 to 1995, under the same 4% withdrawal rule. Green means the portfolio is healthy. Yellow means it is thinning. Red means it is approaching or has reached depletion.

Several patterns emerge:

• The worst cohorts cluster together. Retirees starting in the late 1960s and early 1970s show a progression from green to yellow to red as they pass through the inflationary decade. The damage is not instant; it accumulates gradually as withdrawals compound the effect of weak real returns.
• Some cohorts bleed out slowly. A row might stay green for 15 or even 20 years before shifting to yellow and then red. This is the insidious nature of sequence risk: it can take decades to reveal itself. A retiree 10 years in might feel confident based on their portfolio balance, unaware that the early damage has already sealed their trajectory.
• The best cohorts stay green throughout. Retirees starting in the early 1980s, early 1990s, and mid-2010s benefited from strong early real returns that built such large portfolio cushions that even later downturns barely registered. The 1982 cohort is the most dramatic example, but the pattern is consistent.
• Long-run CAGR does not predict the color pattern. Some rows with relatively high 30-year CAGRs still reach depletion, while some with lower CAGRs survive comfortably. What separates them is the distribution of returns in the first 5-10 years.

This is what makes backtesting so valuable. A single average return (or even a single success rate like "the 4% rule worked 95% of the time") hides the enormous variation underneath. The heatmap forces you to confront the reality that your retirement outcome depends heavily on when you happen to retire, not just how much you have saved.

Why Average Returns Are the Wrong Mental Model

At this point, the natural question is: if averages are misleading, what should a retiree focus on? The answer involves understanding two related but distinct concepts.

Arithmetic mean vs. geometric mean

The arithmetic mean is the simple average of annual returns. The geometric mean (CAGR) accounts for compounding and is always lower. For accumulation-phase investors, the geometric mean is the right summary statistic, because it tells you how fast your portfolio actually grew.

But for retirees making withdrawals, neither mean is sufficient. A portfolio's path matters, not just its destination. Two return sequences with the same geometric mean can produce wildly different outcomes when paired with a fixed withdrawal rule. This is because the geometric mean does not capture the interaction between the timing of returns and the timing of withdrawals.

The first-decade multiplier

Michael Kitces's research on safe withdrawal rates found that the worst outcomes are driven not by single dramatic crashes, but by sustained periods of poor real returns in the first decade of retirement. He identifies the 30-year retirement starting in 1966 as the historical worst case, and traces its failure to the combination of below-average real stock returns and above-average inflation that persisted from the mid-1960s through the early 1980s.

The math behind this is straightforward. Early withdrawals from a declining portfolio create a multiplier effect: each dollar withdrawn during a downturn is a dollar that cannot participate in the eventual recovery. If your portfolio drops 40% and you continue withdrawing, the recovery needs to be proportionally larger just to return to the starting balance, let alone to fund future withdrawals.

A 30% loss requires a 43% gain to break even. A 50% loss requires a 100% gain. When withdrawals are layered on top, the break-even hurdle grows even higher because the recovery is compounding on a smaller base that continues to shrink with each withdrawal.

Where Backtesting Ends and Monte Carlo Begins

Historical backtesting is the foundation of sequence-of-returns analysis. It shows you what actually happened to real retirees in real market conditions, across every possible starting year. There is no modeling assumption or parameter to debate; it is just the data.

But backtesting has a fundamental limitation: it only shows you the sequences that actually occurred. U.S. market history since 1926 gives you roughly 70 overlapping 30-year windows. That is a rich dataset, but it is still just one path through one country's markets. The future may produce return sequences that are worse than, different from, or combinations of historical periods.

This is where Monte Carlo simulation becomes essential. Instead of replaying history, Monte Carlo generates thousands of plausible return sequences (typically 10,000+) drawn from statistical distributions. Each simulation runs your withdrawal rule year by year, producing a distribution of outcomes rather than a single historical track record.

The two methods are complements, not substitutes:

• Backtesting makes sequence risk visceral. The 1966 vs. 1982 comparison, the all-years heatmap, and the scatter of CAGR vs. outcome are concrete and historical. They teach the concept in a way that abstract probability distributions cannot.
• Monte Carlo tests your specific plan. Your portfolio allocation, withdrawal rule, time horizon, and spending flexibility are unique. Monte Carlo lets you see the range of outcomes for your plan, not just what would have happened to a generic portfolio in historical U.S. markets.
• Monte Carlo accounts for scenarios history has not produced. U.S. historical returns have been among the strongest in the world. Investors with globally diversified portfolios, or those planning for the possibility that future U.S. returns may be lower than historical averages, benefit from Monte Carlo's ability to sample from a wider range of outcomes.

A robust retirement plan uses both. Start with backtesting to understand the historical landscape and internalize the risk. Then use Monte Carlo to stress-test your personal plan against a much wider range of possible futures.

What You Can Do About Sequence Risk

Sequence risk is worst when spending is rigid. If you withdraw the same inflation-adjusted dollar amount regardless of market conditions, you have no defense against a bad early sequence. Vanguard's retirement research makes this point directly: dynamic spending strategies that trim withdrawals after poor markets and allow more after strong ones significantly improve portfolio longevity.

Several practical strategies reduce sequence risk exposure:

• Use a dynamic spending policy. Strategies like Guyton-Klinger guardrails, Variable Percentage Withdrawal (VPW), or floor-and-ceiling rules automatically adjust spending in response to market conditions. They sacrifice some income stability for dramatically better survival rates. See the Safe Withdrawal Rate guide for a comparison of five modern withdrawal strategies.
• Build a cash reserve or bond tent. Holding 1-3 years of spending in cash or short-term bonds allows you to avoid selling equities during a downturn. A "bond tent" (temporarily increasing your bond allocation around the retirement date, then gradually shifting back to equities) specifically targets the years when sequence risk is highest.
• Diversify beyond U.S. equities. International stocks, bonds, TIPS, and real assets reduce the probability of a prolonged period of negative real returns in your specific portfolio. Historical U.S.-only data shows the worst sequences; a globally diversified portfolio may have different, and potentially less severe, sequence risk patterns.
• Delay discretionary spending in the first 5 years. If you can keep withdrawals below your planned rate in the critical early years of retirement, you give your portfolio more time to establish a cushion. This does not mean living frugally forever; it means front-loading flexibility when it matters most.
• Monitor and adjust. A retirement plan is not a set-and-forget decision. Reviewing your withdrawal rate, portfolio balance, and spending each year lets you catch unfavorable trends early, long before the damage becomes irreversible.

The point is not to predict which return sequence you will face. No one can. The point is to build a plan that survives the bad ones.

Related Guides

Sequence-of-returns risk connects directly to several other aspects of retirement planning:

• Safe Withdrawal Rate: Why the 4% Rule Isn't Enough explores five modern spending strategies designed to adapt to market conditions, directly addressing the rigidity that makes sequence risk so dangerous.
• Monte Carlo Retirement Simulation: A Complete Guide explains how 10,000+ simulated scenarios stress-test your plan against bad-but-plausible return sequences that may not appear in historical data.
• Lifecycle Asset Allocation covers how your stock/bond mix should evolve as you approach and enter retirement, including the bond tent concept that directly mitigates early-retirement sequence risk.
• How to Determine Your Financial Independence Number shows how your chosen withdrawal rate determines the portfolio size needed for financial independence, a number that sequence risk puts to the test.
• Do Stock Valuations Still Matter? explains why retiring at a high CAPE compounds sequence risk and how to build forward-return assumptions that account for current valuations.

Key Takeaways

• Average returns are the wrong summary statistic for retirees. Two portfolios with nearly identical 30-year CAGRs can produce opposite outcomes when paired with a withdrawal rule. What matters is the sequence of returns, especially in the first decade.
• Sequence risk is driven by weak real returns plus inflation, not just crashes. The worst historical outcomes were not caused by single dramatic market drops, but by sustained periods where low real equity returns coincided with rising inflation, eroding purchasing power from both sides.
• The first 5-10 years of retirement are disproportionately important. Early withdrawals from a declining portfolio permanently reduce the capital base that future gains compound on. This is why the retirement year matters more than most people realize.
• Backtesting and Monte Carlo are complements. Historical data makes sequence risk tangible. Monte Carlo lets you test whether your specific plan survives bad sequences that may differ from historical patterns.
• Flexible spending is the primary defense. Dynamic withdrawal strategies, cash reserves, and global diversification all reduce the damage that a bad return sequence can inflict on a retirement portfolio.