Financial Planning Methods
1. Probability-Based Withdrawal
π What it is:
Uses Monte Carlo simulations to estimate the probability your money will last based on various market conditions.
π Key Features:
Evaluates thousands of possible market scenarios.
Adjusts withdrawals based on projected success rates.
Aims for a target (e.g., 90% probability of success).
β Pros:
Dynamic and responsive to real data.
Helps reduce the risk of running out of money.
β οΈ Cons:
Complex to set up and interpret.
Can lead to large income adjustments if market conditions worsen.
Boldin's Chance of Success estimates the likelihood of your retirement plan lasting through your projected lifespan. This probability is determined by a Monte Carlo simulation involving 1,000 trials. In each trial, investment returns fluctuate monthly to project how likely you are to meet your financial goals.
We encourage you to adjust your Retirement Date, recurring spending, large planned expenses and other elements and view the impact on your Chance of Success.
2. Fixed Withdrawal Rate (e.g., 4% Rule)
π What it is:
You withdraw a fixed percentage of your portfolio each year (commonly 4%), regardless of market conditions.
π Key Features:
Simple to understand and implement.
Based on historical market data.
β Pros:
Predictable and easy to automate.
Popular and widely studied (e.g., Trinity Study).
β οΈ Cons:
Doesnβt adjust for personal spending changes or market performance.
Could overspend in bad years or underspend in good years.
Boldin's Fixed Percentage strategy allows you to set your desired withdrawal rate and start age. The plan takes the portfolio balance in the start year and draws down your desired percent, increased through your lifespan at your general inflation rate. (IE: it does not assess the portfolio balance every year.) Our model includes user entered expenses in withdrawals under this selection, and provides a green plot line to help you compare the fixed percentage to your budgeted expenses.
3. Guardrails Withdrawals (e.g., Guyton-Klinger Rule)
π What it is:
Withdrawals are adjusted based on portfolio performance within preset "guardrails" (limits). If the portfolio grows, you can increase spending; if it drops too much, you reduce it.
π Key Features:
Has a baseline withdrawal (like 4%), but changes only when your portfolio breaches certain thresholds.
Designed to maintain sustainability without frequent micromanagement.
β Pros:
More flexible and sustainable than a fixed rule.
Helps maintain a safe withdrawal rate with market feedback.
β οΈ Cons:
Requires periodic review and discipline to cut spending in down markets.
Boldin's Max Spend strategy allows you to view the impact of depleting all of your accounts down to your legacy goal (or zero if you donβt have one) by longevity age. This is a great place to go for insights about your ability to increase lifestyle spending on wants and wishes and may be considered an upper guardrail.
4. Goal Based
π What it is:
Withdrawals are based on your actual, evolving expenses, rather than formulas. You spend what you need, within reason.
π Key Features:
Focuses on budgeting and adjusting to your lifestyle needs.
Flexible to changing life events (health, travel, etc.).
β Pros:
Most personalized and realistic.
Prioritizes actual life goals over abstract numbers.
β οΈ Cons:
No built-in protection against longevity or market risk.
Requires careful monitoring of portfolio sustainability.
Boldin's default Based on Spending Needs Strategy is a Goal Based strategy. With this selection, the Planner will only withdraw enough to satisfy Required Minimum Distributions and fund any shortfall between the expenses youβve entered in your plan and new income coming in from sources such as work, pensions and Social Security.
π§ Summary Table:
Method | Flexibility | Simplicity | Market Responsive | Risk Management |
Probability Based | Medium-High | Medium | High | High |
Fixed Withdrawals | Low | High | Low | Medium |
Guardrails Spending | Medium | Medium | Medium-High | High |
Goal Based | High | Medium | indirectly | Low-Medium |