QuantCalcResearchDynamic vs. static withdrawal strategies

Dynamic vs. static withdrawal strategies, quantified

Four withdrawal rules — the static 4% rule, a constant 5%-of-balance rule, Guyton-Klinger guardrails, and Variable Percentage Withdrawal — run on the same 10,000 Monte Carlo paths over 35 years. The stability-versus-legacy trade, in numbers.

Guardrails cut the 4% rule’s failure rate from 17% to 1.1% — a 94% reduction — by trading depletion for spending cuts, at a 40% legacy cost. On a 60/40 portfolio over 35 years, the static 4% rule runs out of money on 17% of Monte Carlo paths while paying a perfectly flat real income and leaving a large median legacy ($1.16M). Guyton-Klinger guardrails starting at a higher 5% withdrawal rate drop that failure rate to 1.1% — keeping 98.9% of plans solvent by trading depletion for spending cuts (a typical worst-case real-spending drawdown of 27%), and they do it while spending 15% more over the retirement. The price is legacy: the guardrail plan’s median real ending balance is 40% smaller than the 4% rule’s. This is the quantified companion to our guide on dynamic vs. static withdrawal strategies.

The question

“Dynamic beats static” is easy to say and hard to size. So we ran four withdrawal rules on the identical set of 10,000 Monte Carlo market paths — common random numbers, so every rule faces exactly the same 35-year sequence of returns, and the only thing that differs is the spending rule. The retiree starts at age 65 with $1,000,000, spends for 35 years (to age 100), and everything is measured in real (inflation-adjusted, today’s) dollars. The four rules:

The stability-versus-legacy trade, in one table

Every number below is for the 60/40 stock/bond portfolio, 10,000 paths, 35 years, real dollars. Plan survival is the share of paths that never failed to fund the intended withdrawal (the constant-percentage and VPW rules scale spending to whatever is there, so they are solvent by construction). “Worst-year income” is the 10th-percentile of each path’s leanest year — the downside a bad-luck retiree actually lives through.

StrategyPlan survival (35y)Starting incomeLifetime income (median)Worst-year income (p10)Years with a cutMax spending drawdown (median)Median legacy
Static 4% rule83.0%$40,000$1,400,000$01%0%$1,161,564
Guyton-Klinger guardrails98.9%$50,000$1,611,103$21,27722%27%$702,640
Constant 5% of balance100%$50,000$1,582,068$15,13451%51%$769,013
Variable percentage (VPW)100%$56,384$1,927,489$18,54950%50%$0

How to read it. The static 4% rule is the stability-and-legacy champion — a dead-flat $40,000 real every year and a median $1.16M left over — but it also carries the only real failure risk (17%) and, on the paths where it fails, income falls to $0. The dynamic rules almost never leave a retiree penniless, and they spend more over a lifetime, but they demand flexibility: a cut in one year out of five or more, and (for VPW) essentially nothing left at the end.

What the spending actually looks like

The median real income path makes the personalities plain. The static 4% line is a ruler. The guardrail line starts a quarter higher and stays there with gentle give. The constant-percentage and VPW lines start highest and drift as the portfolio and the amortization schedule dictate.

Line chart of median real annual income by age from 65 to 99 on a 60/40 portfolio, for four withdrawal rules. The static 4% rule is a flat line at $40,000. Guyton-Klinger guardrails start at $50,000 and stay near that level. The constant 5%-of-balance line starts at $50,000 and drifts down. The VPW line starts highest at $56,384 and declines as it amortizes the balance toward zero.

Downside protection: which dynamic rule cuts most gently?

All three dynamic rules avoid outright ruin, but they are not equal on the downside. In a bad-luck retirement (the 10th-percentile worst year), Guyton-Klinger guardrails leave the most on the table — a worst-year real income of $21,277, versus $18,549 for VPW and $15,134 for the constant-percentage rule. Guardrails also ask for cuts far less often: a cut in about 22% of years, against roughly 51% for the constant-percentage and VPW rules. The static 4% rule, by contrast, asks for a cut in only 1% of years — but that number hides the cliff: when it fails, spending does not taper, it collapses.

Scatter plot of four withdrawal strategies on a 60/40 portfolio, with median lifetime real income on the horizontal axis and median real legacy on the vertical axis. The static 4% rule sits low on income but highest on legacy; Guyton-Klinger guardrails and the constant-percentage rule sit higher on income with moderate legacy; VPW sits highest on income but at essentially zero legacy. Each point is labelled with its plan-survival rate.

Does the allocation change the verdict?

We ran the same four rules on three stock/bond mixes. A bond-heavier portfolio lowers both the failure risk and the legacy of the static 4% rule, but the shape of the trade is unchanged: guardrails eliminate almost all of the 4% rule’s failure rate at every allocation by trading depletion for spending cuts, at the cost of a materially smaller median legacy.

AllocationStatic 4% rule — plan survivalGuardrails — plan survivalGuardrails median legacy vs. 4% rule
80/2082.3%97.3%−47%
60/4083.0%98.9%−40%
40/6080.8%99.5%−26%
How to read this study. These are modeled outcomes on forward-looking real capital-market assumptions, not a forecast of any particular market. Everything is a single-portfolio, pre-tax model in real dollars — Social Security, pensions, taxes, fees, and spending shocks (such as late-life health costs) are outside its scope and can all move the answer. “Plan survival” means the portfolio funded every intended withdrawal; it says nothing about whether the resulting spending was comfortable. Read the strategy comparison as a map of trade-offs, not a ranking.

What it implies for your withdrawal plan

  1. The choice is a trade, not a winner. The static 4% rule buys the most predictable spending and the largest legacy, and pays for it with a real (17%) chance of running short. The dynamic rules buy near-certain solvency and higher lifetime spending, and pay for it in spending variability and legacy.
  2. If flexibility is available, guardrails are the balanced middle. They delivered near-certain plan survival (98.9% — close to the guaranteed solvency of the fraction-of-balance rules), the gentlest downside of the dynamic rules, and 15% more lifetime spending than the 4% rule — as long as you can absorb a cut in roughly 22% of years.
  3. Match the rule to the money you can flex. If most spending is essential and hard to trim, the variability of a constant-percentage or VPW rule is hard to live with; if much of it is discretionary, the dynamic rules turn that flexibility into higher average spending and a far smaller chance of ruin.

Run your own numbers

Free: enter your own balance, allocation, and spending, and compare static and dynamic withdrawal rules across 10,000 Monte Carlo simulations — success rate, spending, and legacy, side by side. No signup.

Open the Monte Carlo planner →
Or read the plain-English guide to dynamic vs. static withdrawals →

Methodology

Return model. Each year, five asset-class real returns (US equity, international equity, bonds, real estate, cash) are drawn jointly from a multivariate normal built on long-run real capital-market assumptions and a correlation matrix — the same return model used across QuantCalc research (see the sibling ACA subsidy-cliff study). The portfolio’s real return each year is the allocation-weighted sum, and wealth compounds geometrically (the balance is multiplied by one plus that return). The correlation matrix is validated as positive-semidefinite via its Cholesky factor before any paths are drawn. For each allocation, one set of 10,000 return paths is generated and fed to all four strategies (common random numbers), so differences between strategies are differences in the rule, not in luck. The engine is deterministic: two runs produce byte-identical output (seed 20260711).

The withdrawal rules, exactly as implemented.

Documented assumptions and limitations.

Reproducibility

The full per-allocation, per-strategy results are published as open data under a CC0 public-domain dedication: results.csv and summary.json. The engine (withdrawal-strategies-1.0.0) is deterministic (seed 20260711): two runs produce byte-identical output. Sources: long-run real capital-market assumptions as used across QuantCalc research (see the ACA subsidy-cliff study and our methodology); Guyton & Klinger, Decision Rules and Maximum Initial Withdrawal Rates (Journal of Financial Planning, 2006); the Bogleheads Variable Percentage Withdrawal method; Bengen (1994) and the Trinity study (Cooley, Hubbard & Walz, 1998) for the 4% rule.

FAQ

Do dynamic withdrawal strategies really beat the static 4% rule?

It depends on what you are optimizing. On a 60/40 portfolio over 35 years in this study, the static 4% rule ran out of money on 17% of Monte Carlo paths but paid a perfectly flat real income and left the largest median legacy ($1.16M real). Guyton-Klinger guardrails dropped the failure rate to 1.1% and spent 15% more over the retirement, but left about 40% less legacy and asked for a spending cut in about 22% of years. Dynamic rules win on plan survival and lifetime spending; the static rule wins on predictability and legacy.

How often and how deeply do guardrails cut spending?

In this study, Guyton-Klinger guardrails asked for a real-spending cut in about 22% of years, with a typical (median) worst-case peak-to-trough spending drawdown of 27%. That is gentler than a constant 5%-of-balance rule or VPW, which cut in roughly half of all years. The trade for that flexibility is a much lower chance of depleting the portfolio.

Which withdrawal strategy leaves the most to heirs?

The static 4% rule, by a wide margin: it left a median real ending balance of about $1.16M on a 60/40 portfolio, because it deliberately underspends to stay safe. Guyton-Klinger guardrails left roughly 40% less, and Variable Percentage Withdrawal left essentially nothing — it is designed to spend the portfolio down toward zero by the end of the horizon.

What assumptions does this study use, and can I test my own numbers?

10,000 Monte Carlo paths over 35 years (age 65 to 100), on long-run real capital-market assumptions, with all four rules run on the same return paths (common random numbers). It is a single-portfolio, pre-tax model in real dollars. You can test static and dynamic rules on your own balance, allocation, and spending in the free Monte Carlo planner, which runs in the browser with no signup.

Published 2026-07-09 by QuantCalc Research. Educational research, not financial advice. Related: dynamic vs. static withdrawal strategies (guide) · Withdrawal Strategy Lab · sequence-of-returns risk (Monte Carlo).