A Key Criticism of Monte Carlo is Unfounded
Monte Carlo projections have become the popular way to do financial projections among advisors. Indeed, approximately 80% of financial advisors noted using the tool in a recent Alliance for Lifetime Income survey.
One common criticism I hear from advisors about Monte Carlo (especially from those who don’t use it) is that it incorrectly assumes returns are normally distributed (i.e., follow a perfect bell curve). But concerns around nonnormal returns and Monte Carlo are a red herring (i.e., nonissue) for a variety of reasons.
Perhaps most importantly, it is possible for a return distribution to be nonnormal in a Monte Carlo projection; its whatever distribution is assumed by the user or respective tool. While return distributions may not be perfectly normal at relatively high frequencies (e.g., daily), return distributions become increasingly normal over longer periods (e.g., annually). Finally, financial plans require a significant number of other assumptions that will have a materially greater effect on the outcome (e.g., saving, spending, length of retirement, etc.) than the specific moments of the return distribution of the opportunity set of asset classes.
The next time someone suggests that nonnormal returns are a problem with Monte Carlo, tell them that their concern is a nonissue!
Monte Carlo does it all
Monte Carlo projections are used by financial advisors to illustrate the uncertainty associated with accomplishing various financial goals, such as retirement. For example, in a recent survey I conducted with Prudential Financial, Inc. in February 2023 among 190 financial advisors, 80% of respondents noted using Monte Carlo, a nearly identical percentage as the advisors who noted doing so in the latest Alliance for Lifetime Income 2023 Protected Retirement Income and Planning (PRIP) Study.