We’re Different
We won’t lie to you
If you google "retirement calculator," you'll find plenty of results, many of which seem like nifty tools. They allow you to input basic information like your age, current savings, retirement date, etc. And after you've played 20 Questions with the computer, the program will calculate your result to the tune of something like: “Congrats, Rex. You can retire comfortably at age 62 with a 91% probability.”
Wrong.
Look, we don’t mean to throw stones, but this stuff is important. Some of the biggest players in personal finance offer the worst online investment calculators. These tools often ignore Monte Carlo analysis completely, or shoehorn a bastardized version of it into a format it isn’t appropriate for. One popular website simply uses the performance history of a chosen investment to calculate the size of your eventual nest egg with an assigned “probability” of success.
Alas, you can’t calculate the likelihood of something that doesn’t have a known probability distribution (see here). Suggesting otherwise is foolish and provides folks with a false sense of security.
We’ve got fat tails
We’ve known for 60 years that returns are not normally distributed, yet the bell curve remains the default framework in today’s most popular financial planning software. This is because (i) it’s an easy-to-use and well-understood statistical model, and (ii) investment returns seem to map reasonably well to the bell curve much of the time.
But this approach has dangerous shortcomings. Investing—like life—is vulnerable to low probability and high impact “tail events” (e.g. “Black Swans”) that the normal distribution doesn’t appropriately account for. We see five- or six-sigma fluctuations in monthly return data much more often than we would if returns actually conformed to the classic bell curve. The pandemic sell-off in March 2020 is the most recent example. The implications of these tail events on one’s financial plan can be life-changing. It stands to reason that modern personal finance software should adjust its statistical methods accordingly.
Our program improves upon the traditional Monte Carlo approach by offering multiple probability distributions and time series models. We’ve built a product capable of replicating the statistical characteristics observed empirically (e.g., fat tails). This allows users to run simulations more consistent with the real world.
We can defend our assumptions
Honest Math takes a thoughtful and honest approach to capital market expectations. The expected return on equities, for instance, should be a logical combination of low-risk interest rates (e.g. U.S. Treasury rates) and an equity risk premium. Given that interest rates are hovering near all-time lows today, we must think carefully about the implied risk premiums required to replicate historical stock market performance to the tune of 10-12% annually, and whether that seems reasonable. We also believe capital market expectations should fundamentally reconcile with realistic economic growth prospects and prevailing price levels (P/E ratios).
In short, our approach is in stark contrast to other models that rely purely on historical investment returns to estimate future portfolio performance. This approach ignores the change over time to the broader economic factors that contributed to those prior returns.
We provide better perspectives on risk
It’s common for experts to talk about annual volatility, sorting data neatly from January 1 to December 31 as if there is something statistically magical about the Gregorian calendar. “Stocks have never fallen by more than x% in any year”, for instance. But looking at volatility purely on a calendar year basis can be wildly misleading. Take March 2020—remember that ball of fun? Well, if we look at things strictly from calendar year to calendar year, that volatility gets overlooked because markets have since recovered. We don't think that makes much sense. After all, it was a historically quick and sharp decline that caused many folks to make drastic changes to their portfolios.
Looking at activity on a more granular level—say, from month-to-month—gives us a better idea about how quickly things can change, especially for the worse. When markets are on the calmer side, your portfolio might be the last thing on your mind. But that changes fast when the bottom falls out of stock prices. And it’s in moments like these that folks frequently make decisions that could have long-lasting consequences on their planning, like reallocating their holdings or withdrawing from the market entirely.
In short, since you don't make decisions strictly on a calendar year basis, you probably shouldn't think about risk that way either.
We keep things simple and affordable
All users are just a few clicks away from their own portfolio simulation dashboard. The user interface is simple and intuitive. Assumptions can be toggled and results evaluated within a matter of seconds. State-of-the-art financial planning software starting at free. We think the advantage here is clear.
