Research & Methodology

This is where we show how the planning engine works, what we tested, and what assumptions drive results.

Executive Summary

Our research is built around one practical question:

Which planning decisions materially improve a retiree’s odds of meeting spending goals while controlling tax drag and sequence risk?

What We Tested

• Withdrawal sequencing across taxable, tax-deferred, and tax-free accounts
• Roth conversion timing and bracket management
• Tax-law scenario exposure (including TCJA sunset and post-2025 changes)
• IRMAA threshold effects and Medicare premium drag
• Sequence-of-returns sensitivity across multiple market environments
• Estate and beneficiary impact under current inherited IRA rules

Key Findings

1. Tax-aware withdrawal sequencing can reduce lifetime tax drag versus fixed-order withdrawals.
2. Roth conversions work best when tied to bracket capacity and future RMD pressure.
3. A plan that survives one return model can still fail in other regimes, so cross-model testing matters.
4. Tax parameter flexibility is essential when law changes; static calculators go stale quickly.

Read the Papers

Download the full research package:

Start with the executive summary for the fast version. Use the full white paper for assumptions, model logic, and disclosures.

How We Model

1) Inputs

• User-provided portfolio balances and account types
• Income streams (earned income, pensions, Social Security timing)
• Spending profile by phase (pre-retirement, transition, retirement, late-stage)
• Tax configuration (federal and state settings, deductions, bracket assumptions)
• Policy toggles for scenario analysis (e.g., exemption levels, deduction changes)

2) Model Framework

• Deterministic cash flow projection for baseline plan trajectory
• Monte Carlo simulation for return-path uncertainty and survivability analysis
• Tax engine applied annually to estimate liability and bracket interactions
• Withdrawal policy logic to test sequencing and conversion strategies
• Optional estate projection layer for bequest and heir-tax context

3) Scenario Design

• Baseline scenario representing current strategy
• Alternative scenarios for retirement date, spending level, and allocation shifts
• Targeted tax strategy scenarios (conversion schedules, deduction windows)
• Stress scenarios for adverse return paths and inflation persistence

4) Validation

• Internal consistency checks (cash flow identity and balance transitions)
• Parameter sensitivity checks (single-variable perturbations)
• Edge-case tests around bracket boundaries and threshold cliffs
• Cross-scenario reasonableness review against expected directional outcomes

5) Assumptions

• Return distributions are uncertain and model-dependent
• Inflation can persist outside historical averages
• Tax law can change and requires periodic parameter updates
• Spending behavior is adaptive in real life, even when modeled as static

Limits & Disclosures

• This is planning software, not individualized investment or tax advice.
• Output quality depends on input quality and assumption discipline.
• Monte Carlo probabilities are scenario-dependent estimates, not guarantees.
• Future policy changes can alter outcomes materially.

For implementation decisions, validate results with a qualified CPA, EA, or fee-only fiduciary advisor.

Cite This Work

Fatboy Software. "Fatboy Software Financial Planner White Paper." Version 1.0, March 2026. https://www.fatboysoftware.com/research-methodology

Questions

Questions about assumptions, methodology details, or reproducing a scenario:

• Email: fbfinancialplanner@gmail.com