Monte Carlo Retirement Calculator

How a Monte Carlo Retirement Calculator Works

A Monte Carlo retirement calculator uses randomized simulations to model the range of possible outcomes for your retirement savings. Instead of assuming a fixed return like 7% every year, it generates thousands of different market return sequences based on historical patterns.

The Problem with Simple Projections

A standard retirement calculator might tell you that your $1 million portfolio will grow to $2.5 million by retirement at 7% annual returns. But markets don't return 7% every year. Some years return +25%, others lose -35%. The order of those returns, known as sequence of returns risk, can mean the difference between running out of money at 82 or leaving $3 million to your heirs.

What Monte Carlo Simulation Does Differently

Monte Carlo analysis runs your retirement plan through 5,000 different market scenarios. Each simulation uses randomly generated returns based on historical market behavior, modeled with a log-normal distribution. This captures the natural volatility of real markets, including occasional crashes and booms.

Each simulation also varies inflation rates, so you're not assuming a fixed 3% every year. The result is a probability of success: the percentage of simulations where your money lasts through your planned retirement.

What Is a Good Monte Carlo Success Rate?

Most financial planners consider these benchmarks:

• 90%+ success rate: Very strong plan. You may even be saving too much or spending too conservatively.
• 80-90% success rate: Solid plan with reasonable safety margin. Most planners consider this the sweet spot.
• 70-80% success rate: Workable, but consider adjustments like saving more, spending less, or working a year or two longer.
• Below 70%: Meaningful risk of running out of money. Plan changes are recommended.

Keep in mind that Monte Carlo is not a prediction. A 90% success rate doesn't mean you're guaranteed to be fine. It means that in 90 out of 100 simulated market histories, your money lasted. Rerunning the simulation periodically as you approach and enter retirement helps you stay on track. Start your free plan to see where you stand.

Why Sequence of Returns Risk Matters More Than Average Returns

Sequence of returns risk is the main reason Monte Carlo simulation exists for retirement planning. Two retirees with identical savings, spending, and the exact same average return over 30 years can have dramatically different outcomes based purely on when the bad years happen.

Example: Same Average, Different Outcomes

Consider two retirees, each starting with $1 million and withdrawing $45,000 per year:

• Retiree A experiences strong returns in years 1-5, then a crash in years 6-8. At age 95, they still have $1.4 million.
• Retiree B experiences the crash in years 1-3, then strong returns after. Despite the same average return over 30 years, they run out of money at age 84.

Both retirees had the same average annual return. The difference was timing. When you're withdrawing from your portfolio, early losses are devastating because you're selling assets at depressed prices, leaving less to recover when markets bounce back.

How Monte Carlo Captures This Risk

By running 5,000 simulations with different sequences of returns, Monte Carlo analysis naturally captures this risk. Some simulations start with crashes, some start with booms, and most fall somewhere in between. The success rate tells you how robust your plan is across all these possible futures.

This is the kind of analysis that used to be available only through expensive financial advisors. RetirePlanAI makes it available to everyone for free.

Monte Carlo vs. Historical Market Replay

RetirePlanAI offers both Monte Carlo simulation and historical market replay. Understanding the difference helps you interpret results:

Monte Carlo Simulation (Randomized)

• Generates 5,000 random return sequences based on historical market statistics
• Uses log-normal distribution to model realistic market behavior
• Produces a probability of success and percentile outcomes
• Best for answering: "What are my odds across all possible futures?"

Historical Market Replay (Sequential)

• Uses actual historical returns from 1928 to present
• Shows how your plan would have performed in every historical period
• Tests against real events like the Great Depression, 1970s stagflation, 2008 crash
• Best for answering: "Would my plan have survived every historical crisis?"

Using both methods together gives you the most complete picture. Monte Carlo shows probability; historical replay shows how your plan handles specific real-world crises. Monte Carlo is available on all plans. Historical market replay is available on paid plans.