Kitces published a great article co-authored by Derek Tharp and Income Lab co-founder, Justin Fitzpatrick. In the article they explore how Monte Carlo simulation can actually *understate* retirement income risk relative to historical simulation at probability of success levels commonly used (e.g., 70% to 90%).
Here are a few of the main points:
- While future returns are unknowable, analytic methods such as Monte Carlo and the use of historical returns can both provide advisors more confidence that their clients’ retirement spending will be sustainable.
- Contrary to popular belief, Monte Carlo simulation can actually be less conservative than historical simulation at levels commonly used in practice.
- Incorporating tools that use a range of simulation types and data could provide more realistic spending recommendations for clients.