QuantCalc

Your Information

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Current Age

Retire At

Plan Until

Tax-Aware Mode See your tax savings — free

Savings ($)

Contrib/mo ($)

Spend/yr ($)

Inflation %

Withdrawal Rule

Cash reserve (years)

Units: Return assumptions (CME) and inflation are nominal annual rates (before inflation). Contributions, spending, and chart values are shown in today's dollars — the simulation converts internally so purchasing power stays constant. More on units →

Social Security & Pension

SS ($/yr)

SS Claim Age

Pension ($/yr)

Pension Start Age

Spouse / partner

Spouse Age

Spouse Death (your age)

Spouse SS ($/yr)

Spouse SS Claim Age

Spouse Pension ($/yr)

Spouse Pension Start Age

Survivor Spending (%)

Spouse Pension Survivor (%)

Account Balances

Traditional ($)

Roth ($)

Taxable ($)

Total: $0

Filing Status

Cost Basis %

Medicare Age

State Tax

Medical Inflation %

Annual QCD ($)

Tax-Exempt Interest ($/yr)

Spouse Age (tax)

Lived Apart All Year Yes, apart all year

Household & Mortality

Your Mortality

Spouse Mortality

Spouse Age

Deterministic Spouse Death Age (optional)

On spouse death the simulation flips MFJ → Single filing, halves the standard deduction, and halves the IRMAA thresholds — the "widowhood tax cliff". See widowhood calculator →

Roth Conversion Optimizer

Mode

Start Age

End Age

Roth conversions count as ordinary income — can trigger ACA cliff and IRMAA. How conversions are modeled → If you set a plan here, every candidate order is simulated around it and the results say so. The pre-Medicare Roth Conversion Planner is a separate tool that also prices ACA premium subsidies and healthcare costs.

Life Events

optional ▶

Advanced Modeling PRO

optional ▶

Non-Gaussian returns and regime switching. Each knob widens the tail risk shown in the success-rate distribution.

Fat-Tail Returns (Student-t df)

Student-t variance mixture. Lower df = fatter tails. df=5 roughly matches empirical equity excess kurtosis.

Cranley-Patterson QMC Scrambling

Randomizes the Sobol sequence each run — enables unbiased Monte Carlo error estimates. Single-run results change slightly; averages converge faster.

2-State Regime Switching (Bull/Bear Markov)

Stochastic Inflation PRO

optional ▶

Replace the constant CPI assumption with a data-driven stochastic process. Defaults calibrated on FRED/BLS 1947–present.

Inflation Model

AR(1) adds month-to-month persistence (φ≈0.45). Multi-category lets medical/education/housing compound at their own CPI sub-index rates. Regime switching captures 1970s-style unanchored inflation as a low-probability state.

Per-asset inflation coupling (β)

Applies literature-default inflation betas (Ang/Piazzesi; Bekaert/Wang): stocks −0.30/−0.20, bonds −5.0, real estate +1.0, cash 0. Shifts log returns by −β·(π−π̄) each month.

Asset Allocation

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Mix in % across your asset classes. Periods let you change allocation over time (e.g. more bonds as you age — a glide path). Add a period with +; each period defines a year range. Totals must sum to 100%.

What's each standard asset class?

US Stocks — broad US equity (S&P 500 / total market index)
Intl Stocks — international developed + emerging market equity (MSCI ACWI ex-US)
Bonds — investment-grade fixed income (US Aggregate; mix of Treasuries + IG corporates)
Real Estate — public REITs (FTSE NAREIT All Equity REITs proxy)
Cash — money market / T-bills / short-term Treasury

PRO users can add, remove or rename asset classes (up to 10). Custom classes use your own return / volatility / correlation assumptions from the Market Data panel.

Years 1 to

Total: 100%

Market Assumptions (CME)

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Capital Market Expectations (CME) are forward-looking annual return forecasts published by major asset managers — typically 5-, 10-, or 30-year horizons. QuantCalc pulls assumptions from publicly available research; we don't make our own forecasts. How CME data is used →

Return Expectations

Correlation Matrix

Volatility

Near-term view

Asset	Return	Vol

Applies to the first years of the plan.

Asset	Return	Vol

Empty cells inherit the long-term value. Most houses publish a near-term return and nothing else.

Correlation Matrix

One set for the whole plan — it is not split by horizon. Edit upper triangle (lower mirrors)

Source publications (verify any number we use)

Each source publishes annually-or-quarterly. The Refresh button pulls the latest dataset we've curated; the Compare button lets you run the same plan against every source side-by-side.

Portfolio Optimizer

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Goal

Glide Path Strategy (up to 3 periods)

Years: to

--%

Success Rate

Based on 100 Monte Carlo simulations · How this works →

10th Pctl

$--

Median

$--

90th Pctl

$--

All dollar values are inflation-adjusted to today's dollars (real $). Why?

Recommended Order

$--

Traditional-First

$--

Advantage of the recommended order (present value)

$--

Methodology: spending is after tax — each year's withdrawal covers spending plus that year's federal, state and Medicare-surcharge bill, paid from the accounts drawn. Several whole-retirement policies — withdrawal orders, and bracket-fill Roth-conversion rules unless you entered your own plan — are simulated on the same market paths; the recommended one has the lowest present value of lifetime tax (each year's bill discounted at the portfolio's own return, plus tax still owed on any traditional balance at the end, valued at an heir's single-filer rate over ten years, plus any spending the portfolio could not fund). The two lifetime-tax figures are medians of tax paid in today's dollars; the saving is paired per path. Details

Assumptions used in this result — click to expand

Run a simulation to see the exact assumptions behind your result.

Portfolio Projection

Allocation

Monte Carlo Paths

Run simulation to see individual paths

Glide Path ?How your asset allocation shifts over time (e.g., more bonds as you age)

Income vs Spending

Run simulation to see income vs spending

Ruin Probability ?The chance your portfolio hits $0 at each point in retirement

Run simulation to see ruin probability

What-if comparisons ?Each row is a full simulation of the plan at the same path count, through the same engine as the Run button. Claiming ages restate the benefit through the primary insurance amount with SSA factors. Scenarios are snapshots of the whole input set, saved in this browser.

Social Security claiming age Full retirement age

Scenarios

Portfolio Projection

Allocation

Monte Carlo Paths

Glide Path ?How your asset allocation shifts over time (e.g., more bonds as you age)

Income vs Spending

Ruin Probability ?The chance your portfolio hits $0 at each point in retirement

What-if comparisons ?Each row is a full simulation of the plan at the same path count, through the same engine as the Run button. Claiming ages restate the benefit through the primary insurance amount with SSA factors. Scenarios are snapshots of the whole input set, saved in this browser.

Account Depletion

Tax Burden

IRMAA Zones ?Medicare surcharge zones based on your projected MAGI. Green = safe, Yellow = near cliff, Red = surcharge applies.

Portfolio Projection

Allocation

Monte Carlo Paths

Glide Path ?How your asset allocation shifts over time (e.g., more bonds as you age)

Income vs Spending

Ruin Probability ?The chance your portfolio hits $0 at each point in retirement

What-if comparisons PRO ?Each row is a full simulation of the plan at the same path count, through the same engine as the Run button. Claiming ages restate the benefit through the primary insurance amount with SSA factors. Scenarios are snapshots of the whole input set, saved in this browser.

Account Depletion

Tax Burden

IRMAA Zones ?Medicare surcharge zones based on your projected MAGI. Green = safe, Yellow = near cliff, Red = surcharge applies.

What-if comparisons ?Each row is a full simulation of the plan at the same path count, through the same engine as the Run button. Claiming ages restate the benefit through the primary insurance amount with SSA factors. Scenarios are snapshots of the whole input set, saved in this browser.