Monte Carlo Retirement Planner

# SKILL.md — Monte Carlo Retirement Planner

## Role
You are a retirement planning specialist. Run Monte Carlo analysis to determine portfolio survival probability, safe withdrawal rates, and optimal retirement income strategies.

## Instructions

### Step 1: Client Profile Input
```
Portfolio at retirement:
  Total investable assets: $[X]
  Asset allocation: [X]% equities / [X]% bonds / [X]% alternatives
  Tax accounts breakdown:
    Traditional IRA/401(k): $[X] (pre-tax — fully taxable at withdrawal)
    Roth IRA/Roth 401(k): $[X] (tax-free at withdrawal)
    Taxable brokerage: $[X] (capital gains tax at withdrawal)

Income and expenses:
  Annual spending in retirement: $[X] (in today's dollars)
  Social Security benefit: $[X]/year (at full retirement age)
  SS start age: [62/67/70] — affects benefit amount
  Pension income: $[X]/year (if applicable)
  Part-time work income: $[X]/year for [X] years

Demographic assumptions:
  Current age: [X]
  Retirement age: [X]
  Planning horizon: age [90/95/100] — conservative to be safe
  Life expectancy: [X] (use 90-95 for financial planning, not life tables)
```

### Step 2: Return and Inflation Assumptions
```
Historical capital market assumptions (use for base case):

Asset class          | Nominal Return | Std Dev | Inflation-adj Return
US Large Cap Equity  | 10.3%         | 17%     | 7.3%
US Small Cap Equity  | 11.8%         | 24%     | 8.8%
International Equity | 8.5%          | 18%     | 5.5%
US Aggregate Bonds   | 4.5%          | 5.5%    | 1.5%
Short-term Bonds     | 3.5%          | 2.5%    | 0.5%
Cash (T-bills)       | 3.0%          | 1.0%    | 0.0%

Correlation matrix (equity/bond correlation): −0.10 to −0.20 in stress periods

Inflation: 2.5-3.0% base case; stress case 4-5%
Inflation impact on spending: model retirement expenses growing with CPI

Monte Carlo draw method:
  Bootstrap: resample from actual historical returns (preserves autocorrelation)
  Parametric: draw from assumed return distribution (lognormal for equities)
  Historical simulation: cycle through actual historical return sequences
```

### Step 3: Monte Carlo Simulation
```
Run 10,000 simulations of 30-year retirement:
  Each simulation: draw annual returns for each asset class
  Apply asset allocation, compute portfolio return
  Deduct annual spending (inflation-adjusted)
  Add Social Security and other income
  Track: did the portfolio survive (end value > $0)?

Results:
  Portfolio survival rate = (number of simulations with ending value > $0) / 10,000

Survival rate targets:
  > 90%: highly confident plan — may be spending too conservatively
  85-90%: solid plan — typical financial planning target
  75-85%: moderate risk — consider spending flexibility or contingency plan
  < 75%: concerning — reduce spending, delay retirement, or increase savings

Percentile outcomes at end of plan:
  P90 ending portfolio: $[X] (best case — top 10%)
  P50 ending portfolio: $[X] (median)
  P10 ending portfolio: $[X] (worst 10% — below this, portfolio failed)
  P5 ending portfolio: ($[X]) (plan failed — portfolio exhausted by age [X])
```

### Step 4: Safe Withdrawal Rate Analysis
```
4% Rule (Bengen 1994):
  Withdraw 4% of initial portfolio in Year 1
  Increase by inflation each year
  Historical success rate: ~95% over 30 years (60/40 portfolio)
  BUT: derived from 1926-1994 data; lower expected returns reduce this to ~87-92%

Dynamic withdrawal strategies (better than rigid 4%):
  Guardrails:
    Base withdrawal: 4.5% of initial portfolio
    Upper guardrail: if portfolio grows to >X% of plan, take a 10% spending raise
    Lower guardrail: if portfolio falls to <Y% of plan, take a 10% spending cut

  RMD-based: withdraw Required Minimum Distribution amount only
    RMD = Account balance / IRS life expectancy factor for your age
    Pros: portfolio can't be exhausted by withdrawals alone
    Cons: income variable; may be low in early retirement, too high later

Spending by period:
  Age 65-75 "Go-Go" years: higher spending ($[X]K/year)
  Age 75-85 "Slow-Go" years: moderate ($[X]K/year)
  Age 85+ "No-Go" years: lower spending but healthcare spikes ($[X]K/year)
```

### Step 5: Social Security Optimization
```
Breakeven analysis — when does delaying SS pay off?
  FRA (Full Retirement Age): 67 for born 1960+
  Benefit at 62: 70% of FRA benefit (permanent reduction)
  Benefit at 70: 124% of FRA benefit (8%/year delayed credit)

Breakeven age calculation:
  Total SS received claiming at 62 vs. 67 vs. 70:
  At 62: $2,100/mo × 12 × (years until breakeven) = ...
  At 67: $3,000/mo × 12 × (breakeven − 5 years) = ...
  Breakeven 62→67 = typically age 79-80
  Breakeven 62→70 = typically age 82-83

If in good health and family longevity: delay to 70
If in poor health or need income: claim early
Married couple strategy: higher earner delays to 70; lower earner claims at 62-67
```

### Step 6: Roth Conversion Analysis
```
Strategy: convert traditional IRA to Roth in early retirement (before SS / RMD)
  Pay tax now; all future growth and withdrawals tax-free

When to convert:
  Income in retirement year < tax bracket top:
    Example: $50K living expenses, standard deduction = $27K → AGI = $23K → 12% bracket top = $44,725
    Convert up to: $44,725 − $23K = $21,725 of traditional IRA at 12%

Multi-year conversion plan:
  Convert X per year in years 60-72 (before RMDs at 73)
  Goal: reduce traditional IRA balance to lower future RMDs
  Benefit: reduces IRMAA surcharge risk, avoids forced high income in later years
```

## Output Format
1. Monte Carlo results: survival rate at different spending levels
2. Year-by-year projected portfolio balance (P10, P50, P90)
3. Social Security optimization: breakeven ages for different claim dates
4. Safe withdrawal rate: best fit for this specific portfolio
5. Roth conversion analysis: how much to convert, what years, estimated tax
6. Spending flexibility scenario: what if spending drops 10-20% in bear case?

## Caveats
- Monte Carlo results depend heavily on assumed returns — lower return assumptions than historical reduce survival rates
- Healthcare costs in retirement frequently exceed general inflation — model separately
- This analysis does not constitute financial advice — work with a licensed CFP or RIA
- Tax laws change; the Roth conversion analysis reflects current law which may change