Scenario Planning for Best, Base, and Worst Cases

advancedPublished: 2025-12-30

Financial planning requires acknowledging uncertainty. Markets fluctuate, employment situations change, and health events occur without warning. Rather than creating a single projection that assumes everything proceeds as expected, sophisticated planning models multiple scenarios to stress-test your financial resilience. This guide explains how to construct base, best, and worst-case scenarios, interpret Monte Carlo simulation results, and develop contingency triggers that protect your financial security.

The Three-Scenario Framework

Base Case: Expected Trajectory

The base case represents your most likely outcome given reasonable assumptions about returns, spending, and life circumstances.

Base Case Assumptions:

  • Investment returns: Long-term historical averages adjusted for current valuations
  • Inflation: 2.5% annually (Federal Reserve target with buffer)
  • Spending: Current lifestyle maintained, adjusted for inflation
  • Income: Continued employment at current trajectory
  • Retirement: Planned age (often 65–67)
  • Social Security: Claiming at full retirement age
  • Health: Standard aging assumptions, Medicare at 65

Setting Return Expectations:

Historical returns provide context, but forward-looking estimates should account for current conditions.

Asset ClassHistorical (1926–2024)Current Forward Estimate
US Large Cap10.3% nominal6.5–7.5% nominal
US Small Cap11.9% nominal7.0–8.5% nominal
International Developed8.1% nominal6.0–7.0% nominal
US Aggregate Bonds5.2% nominal4.0–5.0% nominal
60/40 Portfolio8.5% nominal5.5–6.5% nominal

Lower forward estimates reflect elevated equity valuations and normalized interest rates compared to the 40-year bond bull market.

Best Case: Favorable Conditions

The best case models outcomes when multiple factors align positively, allowing for accelerated goal achievement or enhanced lifestyle.

Best Case Assumption Adjustments:

FactorBase CaseBest Case
Investment returns6% real8% real
Spending growthInflation (2.5%)Below inflation (1.5%)
Income growth2% real4% real
Retirement age6562
Health costsAverageBelow average
WindfallsNoneInheritance or bonus

Best Case Uses:

  • Identify early retirement feasibility
  • Quantify "upside" potential for motivation
  • Determine when to increase charitable giving
  • Evaluate lifestyle enhancement options

Worst Case: Stress Testing

The worst case models adverse conditions to identify vulnerabilities and necessary contingencies.

Worst Case Assumption Adjustments:

FactorBase CaseWorst Case
Investment returns6% real2% real (or sequence of returns risk)
Market declineNone-40% in year 1 of retirement
SpendingPlanned120% of planned (health events)
IncomeContinuedJob loss at age 55, 12-month gap
Retirement age6565 (cannot delay)
Social SecurityFull77% (trust fund depletion adjustment)
Long-term careNone3-year facility stay

Key Stress Events to Model:

  1. Sequence of Returns Risk: Major market decline in early retirement years
  2. Involuntary Early Retirement: Job loss or health issue forcing early exit from workforce
  3. Healthcare Shock: Major illness requiring extended treatment or long-term care
  4. Longevity Risk: Living to 95+ with portfolio depletion concerns
  5. Inflation Spike: Sustained 5%+ inflation eroding purchasing power

Monte Carlo Simulation Interpretation

How Monte Carlo Works

Monte Carlo simulation runs thousands of randomized scenarios, varying investment returns according to historical patterns or specified distributions. Each trial produces a different sequence of returns, allowing the model to estimate the probability of achieving various outcomes.

Key Inputs:

  • Starting portfolio value
  • Annual contributions or withdrawals
  • Asset allocation and associated return/volatility assumptions
  • Time horizon
  • Target ending value or income stream

Output:

  • Probability of success (reaching target or not depleting assets)
  • Distribution of ending values (median, 10th percentile, 90th percentile)
  • Year-by-year confidence intervals

Interpreting Success Rates

Success RateInterpretationRecommended Action
95%+Very high confidence, potentially overfundedConsider increasing spending or earlier retirement
85–95%High confidence, on trackMaintain current plan
75–85%Good confidence with flexibility requiredBuild contingency triggers
65–75%Moderate confidence, adjustments likely neededIdentify specific adjustments now
Below 65%Low confidence, plan changes requiredIncrease savings, delay retirement, or reduce spending

Important Considerations:

  • Monte Carlo success rates are estimates, not guarantees
  • Historical return sequences may not predict future patterns
  • Input assumptions significantly affect outputs
  • Success rates near 100% may indicate excessive conservatism
  • Most planners target 75–90% success, allowing for flexibility

Percentile Analysis

Rather than focusing solely on probability of success, examine the distribution of outcomes.

Example Output:

PercentileEnding Portfolio ValueInterpretation
90th$3,200,000Excellent outcome, 10% chance of exceeding
75th$2,400,000Good outcome
50th (Median)$1,650,000Most likely single outcome
25th$980,000Below average but acceptable
10th$420,000Poor outcome, 10% chance of worse
5th$180,000Very poor outcome, approaching depletion

The spread between percentiles indicates volatility of outcomes. Wider spreads suggest higher-risk portfolios or longer time horizons.

Worked Example: Retirement Projections Under Three Scenarios

Client Profile:

  • Margaret (58) and David (56)
  • Combined income: $245,000
  • Current portfolio: $1,850,000
  • Annual savings: $65,000 (until retirement)
  • Planned retirement: Margaret at 65, David at 65
  • Target annual spending: $130,000 (today's dollars)
  • Social Security (combined at 67): $68,000
  • Required portfolio withdrawal: $62,000/year at retirement (inflation-adjusted)

Base Case Projection

Assumptions:

  • Investment return: 5.5% nominal (3% real after 2.5% inflation)
  • Retirement age: Margaret 65, David 65 (7 years)
  • Spending: $130,000 inflation-adjusted
  • Social Security: Claimed at 67

Projection:

YearAge (M/D)Portfolio StartContributionsGrowth (5.5%)WithdrawalsYear End
158/56$1,850,000$65,000$105,325$0$2,020,325
360/58$2,207,000$65,000$124,960$0$2,396,960
562/60$2,619,000$65,000$147,545$0$2,831,545
764/62$3,091,000$65,000$173,545$0$3,329,545
865/63$3,329,545$0$183,125$133,575$3,379,095
1067/65$3,470,000$0$190,850$140,540$3,520,310

Note: Social Security begins year 10 ($68,000), reducing portfolio withdrawals to $72,540.

YearAge (M/D)WithdrawalSS IncomePortfolio Balance
1572/70$83,250$76,500$3,180,000
2077/75$93,800$86,200$2,690,000
2582/80$105,700$97,100$2,020,000
3087/85$119,100$109,400$1,180,000
3592/90$134,200$123,200$140,000

Base Case Result: Portfolio sustains withdrawals to approximately age 93/91. Monte Carlo success rate: 82%.

Best Case Projection

Assumption Adjustments:

  • Investment return: 7.5% nominal (5% real)
  • Spending: Grows at 2% (below 2.5% inflation)
  • Retirement: Margaret at 63, David at 63 (5 years)
  • Both delay Social Security to 70 for 24% increase

Key Milestones:

MilestoneBest CaseBase Case
Portfolio at retirement$2,831,000$3,329,000
Retirement age63/6165/63
Social Security annual$84,300 (delayed)$68,000
Portfolio at age 85$2,850,000$1,180,000
Monte Carlo success rate96%82%

Best Case Opportunities:

  • Early retirement at 63 feasible with 90%+ success rate
  • Potential to increase spending to $145,000 with 85% success
  • Legacy portfolio of $2M+ likely at life expectancy
  • Charitable giving capacity of $30,000/year without affecting security

Worst Case Projection

Stress Scenario 1: Market Crash at Retirement

Assumptions:

  • 40% market decline in year 1 of retirement (year 8)
  • Returns normalize to 5.5% thereafter
YearEventPortfolio Impact
7End of accumulation$3,329,000
8-40% decline + withdrawal$1,864,000
95.5% recovery + withdrawal$1,828,000
10SS begins, reduced withdrawal$1,850,000

Recovery trajectory shows portfolio stabilizing but remaining $1.5M below base case for 15+ years.

Monte Carlo success rate with sequence risk stress: 68%

Stress Scenario 2: David Job Loss at 60

Assumptions:

  • David loses job at age 60, 18-month unemployment
  • Income drops from $245,000 to $140,000 for 18 months
  • Retirement savings pause during unemployment
  • Portfolio withdrawal of $50,000 to cover income gap

Impact:

  • Portfolio reduced by $130,000 (lost contributions + withdrawal)
  • Retirement delayed to age 67 for both
  • Monte Carlo success rate: 74%

Stress Scenario 3: Long-Term Care Event

Assumptions:

  • David requires memory care at age 80
  • Cost: $8,500/month for 4 years = $408,000 total
  • No long-term care insurance

Impact:

  • Additional $408,000 withdrawn from portfolio ages 80–84
  • Portfolio depletes at age 88/86 instead of 93/91
  • Monte Carlo success rate: 61%

Scenario Comparison Summary

MetricBest CaseBase CaseWorst Case (Combined)
Retirement age63/6165/6367/65
Starting retirement portfolio$2,831,000$3,329,000$2,800,000
Annual spending supported$145,000$130,000$115,000
Portfolio at age 85$2,850,000$1,180,000Depleted
Monte Carlo success rate96%82%58%

Building Contingency Plans

Contingency Triggers

Establish specific thresholds that activate contingency responses:

TriggerThresholdContingency Response
Portfolio decline-25% from peakReduce spending by 10% for 2 years
Portfolio decline-35% from peakReduce spending by 20%, defer discretionary expenses
Monte Carlo successFalls below 70%Implement spending reduction or income generation
Withdrawal rateExceeds 5.5%Reduce spending to sustainable level
Healthcare costsExceed budget by 50%Activate long-term care plan, evaluate downsizing

Spending Flexibility Analysis

Identify discretionary vs. essential spending to understand flexibility:

CategoryAnnual AmountClassificationReducibility
Housing (mortgage/taxes)$28,000EssentialLow (unless downsize)
Healthcare$18,000EssentialLow
Food and household$15,000EssentialModerate (10–20%)
Transportation$12,000EssentialModerate (one car option)
Utilities and insurance$8,000EssentialLow
Travel$20,000DiscretionaryHigh (50–100%)
Entertainment/dining$12,000DiscretionaryHigh (50–75%)
Gifts and charity$10,000DiscretionaryHigh (50–100%)
Miscellaneous$7,000MixedModerate (25–50%)
Total$130,000
Essential spending$81,000
Discretionary spending$49,000

Spending could reduce to $85,000–$95,000 if necessary, providing significant buffer against adverse scenarios.

Sample Review Cadence for Scenario Planning

FrequencyActivity
AnnuallyFull three-scenario review with updated assumptions
QuarterlyPortfolio performance vs. projections
Market decline >15%Ad-hoc scenario stress test
Major life eventImmediate scenario recalculation
Every 3 yearsComprehensive assumption review and reset

Scenario Planning Checklist

Base Case Development

  • Document current return assumptions with sources
  • Specify inflation assumption (typically 2.5–3%)
  • Confirm spending reflects actual current lifestyle
  • Include all income sources with start dates
  • Model Social Security with personalized estimates
  • Run Monte Carlo with 1,000+ trials

Best Case Analysis

  • Increase return assumptions by 1.5–2% above base
  • Model spending growth below inflation
  • Evaluate early retirement feasibility
  • Identify wealth threshold for lifestyle enhancements
  • Calculate charitable giving capacity
  • Document opportunities unlocked by favorable outcomes

Worst Case Stress Testing

  • Model 40% market decline in first retirement year
  • Stress test job loss scenario (12–24 month unemployment)
  • Include healthcare shock ($200,000–$500,000 event)
  • Model long-term care scenario (3–5 years of care)
  • Test Social Security reduction to 77% of projected
  • Calculate minimum portfolio needed for essential spending

Contingency Planning

  • Establish portfolio decline triggers with specific responses
  • Document spending reduction capacity (discretionary vs. essential)
  • Identify potential income generation options
  • Evaluate home equity as emergency reserve
  • Review long-term care insurance options
  • Create decision tree for major stress events

Ongoing Monitoring

  • Track portfolio against scenario projections quarterly
  • Update Monte Carlo inputs annually
  • Recalculate scenarios after major market moves
  • Adjust assumptions when economic conditions shift
  • Review contingency triggers after each annual update
  • Document all assumption changes with rationale

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