10/13/2026
Be careful using DIY retirement planning tools when holding individual stocks. A key characteristic common to this category—is one that isn’t well understood or, for that matter, even surfaced or made particularly easy to understand.
Most tools—pick your flavor—use Monte Carlo simulations built on symmetric return distributions, typically simulating outcomes along a normal or lognormal curve defined by a mean and standard deviation. That’s the industry-standard approach. It’s generally well-suited to diversified portfolios, and the modeling continues to improve.
The reason behind the built-in limitation is practical: these engines are designed around broad asset classes—U.S. equities, international equities, bonds—not individual concentrated positions. A symmetric distribution can be a reasonable approximation for a diversified index fund. The limitation becomes more significant when a portfolio contains a concentrated position, particularly in a single high-volatility stock. Individual-stock returns exhibit skewness and fat tails that a simplified model may not adequately capture.
So it’s not that any one planner is uniquely flawed. The limitation is characteristic of the category: these tools are primarily engineered for diversified funds-level portfolios, while concentrated individual-stock positions are an edge case the symmetric-distribution models simply don't handle well.
Most users never realize their Monte Carlo number is quietly assuming a fat right tail while ignoring or—at best—understating the fat left tail of their holdings.
