Adjust the inputs to see how long your savings will last and how much you need to retire.
About you
Savings & income
$
$
Retirement spending
$
$
%
Grosses up portfolio withdrawals to cover income tax. Enter 0 for Roth accounts or if your spending inputs are already pre-tax.
Portfolio mix & returns
% / 30%
%
%
%
%
Auto-derived from your allocation (stocks σ ≈ 17%, bonds σ ≈ 6%). Override for custom scenarios. When a bond tent is active, MC uses per-year σ based on that year's allocation.
Bond tent
%
yrs
At retirement the portfolio shifts to the peak bond allocation, then gradually reverts to your target mix over the specified years. This cushions early-retirement sequence-of-returns risk at the cost of slightly lower expected returns. For a true tent, peak bond % should exceed your current bond allocation.
Blended portfolio return
–
Real (after inflation): –
Portfolio at retirement
–
In today's $: –
Nest egg needed
–
Today's $ to fund through age 95
Surplus / shortfall
–
in today's $
Probability of success
–
Monte Carlo, 1,000 simulations
Earliest breakeven retirement age
–
–
Portfolio value over time Bond tent active
MC P5–P95MC P25–P75 (core)Constant returns (today's $)
Year-by-year projection (deterministic)
Age
Year
Stocks %
Contribution
Investment returns
Spending
SS/Pension
Portfolio withdrawal
Net impact
Portfolio (nominal)
Portfolio (today's $)
How this model works
Each year the portfolio earns a blended return based on that year's stock/bond allocation. During working years, contributions are added (and grown with inflation). Starting at retirement, you withdraw the amount needed to cover spending (also inflation-adjusted) minus any Social Security or pension income.
Volatility is auto-derived from your allocation using a two-asset portfolio formula (stocks σ ≈ 17%, bonds σ ≈ 6%, correlation ρ ≈ −0.10), giving ~12% for a 70/30 portfolio. You can override the σ field for custom scenarios.
Bond tent: When enabled, the portfolio shifts to a higher bond allocation at retirement to cushion sequence-of-returns risk, then glides back to your target mix over the specified years. Both the deterministic line and the Monte Carlo simulation use the time-varying allocation — so reduced volatility during the tent period is reflected in the MC bands. This typically raises success probability in early retirement at a small cost to long-term expected returns.
The blue line is the deterministic (constant average returns) path. The green band shows the Monte Carlo interquartile range (P25–P75): 1,000 simulations where each year's return is drawn from a normal distribution centred on that year's blended return with the corresponding σ. Probability of success is the share of MC simulations where the portfolio survives to your plan-to age.
"Today's dollars" divides nominal balances by cumulative inflation. The "nest egg needed" is the present-value lump sum to fund all net withdrawals through plan age (discounted at the target-allocation real return).
Limitations: Returns are assumed normally distributed (no fat tails), no taxes (use the tax rate input to gross up), no healthcare shocks, no RMDs. The ~4% rule is a common rule of thumb for a 70/30 US portfolio.