The Long Term Investor Inside the Engine: The Assumptions Behind Your Monte Carlo Retirement Plan (EP.240)
Jan 21, 2026
Delve into the hidden mechanics of your retirement plan's success probability! Discover the three key inputs driving Monte Carlo analysis and why advisors have varying capital market assumptions. Learn how sticking to long-term historical averages can minimize forecasting errors and enhance planning. Peter emphasizes simplicity in assumptions, critiques common approaches, and highlights areas that can genuinely improve financial outcomes. It's a fascinating look at making your retirement strategy more robust!
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Three Inputs Power Monte Carlo Models
- Monte Carlo sims need three market inputs: expected return, volatility, and correlation.
- These capital market assumptions define the range of possible market outcomes, not exact predictions.
What Each Capital Market Input Means
- Expected return is the long-term geometric (compounded) average the model uses.
- Volatility and correlation shape yearly outcome ranges and how assets move together.
Identify Which CMA Approach Your Advisor Uses
- Advisors commonly use four approaches: vendor defaults, building blocks, institutional views, or historical averages.
- Evaluate which approach your planner uses because each yields different Monte Carlo inputs.
