QuantCalc

Portfolio Stress Tester
Retirement Planner Blog Pricing FREE
Stress Scenarios Click to toggle (max 5)
Select scenarios and click Run Stress Test
Scenario Comparison
Scenario Success Rate Median Final 10th Pctl 90th Pctl Max Drawdown
Breaking Point Finder PRO

Find the maximum equity decline your portfolio can survive while maintaining your target success rate.

Click to analyze your portfolio resilience

Portfolio Projection (Median + 10th-90th Percentile Band)

Success Rate Comparison

Ruin Probability Over Time

Correlation Matrix — Base Case

ACA & IRMAA Impact PRO

How Stress Scenarios Affect Healthcare Costs

Under stress scenarios, portfolio drawdowns may force larger withdrawals from tax-deferred accounts (Traditional IRA/401k), pushing your Modified Adjusted Gross Income (MAGI) higher. This can trigger:

ACA Subsidy Cliff: If your MAGI exceeds 400% of the Federal Poverty Level ($62,600 single / $84,600 couple in 2026), you lose all premium tax credits — potentially a $15,000–$25,000 annual cost increase.

IRMAA Surcharges: Medicare Part B/D premiums increase at MAGI thresholds ($106,000 single / $212,000 couple), adding $1,000–$5,000+ per year per person.

Roth Conversion Strategy: Stress scenarios may change your optimal Roth conversion ladder timing. Converting during a downturn (lower account values) can be tax-efficient, but only if MAGI stays below cliff thresholds.

Use the ACA Cliff Calculator →  ·  Full Tax-Aware Planner →

How It Works

Correlated Monte Carlo Simulation
Each scenario uses Cholesky decomposition to generate correlated asset class returns from the correlation matrix. This means when stocks crash, bonds and real estate behave realistically based on their historical co-movements — not independently.

Why it matters: In a crisis, correlations spike. Assets that normally diversify each other start falling together. The 2008 scenario models this with a 0.95 US/Intl correlation (vs 0.85 normally), showing the true stress on a diversified portfolio.

Math: Given correlation matrix C, we compute the Cholesky factor L where C = L·LT. Independent standard normals Z are transformed to correlated normals X = L·Z. Asset returns are then ri = μi + σi·Xi.

Full methodology →