What makes this tool different? The advantage of this one is that it incorporates mortality risk – the uncertainty associated with how long you will live.
Classic tools assume a single age (or ages for a couple) of death for a person. To be conservative, an advanced age such as 95 is used. To be fair, there are good reasons to do this. If the probability of success is high assuming you live to 95, then your chances are good. Here’s the problem. It doesn’t actually produce the chance of running out of money – it produces the probability of running out of money if you live to 95, which most people don’t. Having sufficient funds to live to 95 means you will likely leave money on the table.
Our approach tests your capital sufficiency, meaning are you saving enough, considering a range of possible ages of death weighted by their likelihood. You can still choose to focus on the ones where you live beyond actuarial expectations. Our tool lets you see the impact of mortality – that is how your longevity impacts your rate of success.
The tool on this site philosophically differs in another way. The question “Will you outlive your money?” requires predicting the future. Investment returns, inflation, and mortality are uncertain and hard to predict. One can only hope for an approximate answer. There are other factors such as future tax rates that are also uncertain. Our philosophy is to accept and acknowledge that this exercise is imprecise. Other tools may try to calculate future taxes and such to the penny. Our criticism of this is 1) it may give a false sense of precision; and 2) it requires more time and effort to supply the inputs.
Predicting future wealth is inherently uncertain, like tossing a coin with a 50% chance of landing heads and a 50% chance of landing tails. Providing precise details about the coin’s weight, the force of the toss, the air resistance, and other factors does not significantly improve the accuracy of the prediction. The inherent randomness of the event means that these details do not contribute meaningfully to predicting the outcome. We believe that a lot of time and effort is wasted on certain investment planning details, so we keep the inputs simple. Besides saving time, our approach recognizes the imprecision of the result. Imagine a coin flipping predicting calculator with inputs for the coin’s weight, force of toss and humidity. It might feel more precise even though it’s not. We want you to understand that this calculator produces a ballpark estimate.
There’s more than one way to skin this cat (who skins cats)? When it comes to producing the rates of return to use in this calculator, we offer three general approaches: statistical, random historical, and chronological. Given the nature of the problem, we think attacking it with several approaches allows for a more robust conclusion. Here’s a description of the three methods.
Statistical – Random returns are generated according to a log-normal distribution. The input is an arithmetic mean and a standard deviation. That’s some detail for the quantitatively trained. For those who aren’t, we input an average return (the mean) and a measure of dispersion (standard deviation) that accounts for the fact that returns will vary from the average. We use a log-normal because it’s been widely used in finance (e.g., the Black-Scholes options pricing model) as reasonable for what we are doing.
Random Historical – Underneath the hood of our calculator is a table with monthly returns of U.S. stocks, bonds and inflation going back to 1926. The computer randomly selects months and links them together to form returns for a year. One option you have is to specify whether you link 1, 2, 3, 4, 6, or 12 months to form a year. Using a smaller value allows for a greater range of outcomes because theoretically it could repeatedly pick all of the highest or lowest returns. On the other hand, if you believe that the return in one month depends on the return in a previous month, then you should choose a higher value. We know of no research that indicates you can predict the next month’s stock or bond return based on the previous month’s. However, future inflation is related to past inflation. Feel free to try a few different values.
Chronological – This method actually answers a slightly different question. Rather than “Will you outlive your money?”, this approach answers “How long will my money last?”. The first two consider how long you live. This approach does not. This approach starts with the returns and inflation rates as if you started investing in January 1926 and tests how long your money lasts up to a specified limit (e.g., 40 years). That’s one trial. Then if repeats the process as if you started in February 1926. The result is that we can see how long your money would have lasted 40 years, 30 year or whatever based on history (disclosures).
You can select the range of history for the random historical and chronological methods. That is, you could start in 1946 instead of 1926. Play with it.
Our opinion (everyone is entitled) is that future stock returns are likely to be lower on average than the long-term history. Stocks were considered much more of a speculative investment in 1926 than they are today. They offered a higher dividend yield which is a valuation measure than today even adjusting for share buybacks. We are off the gold standard, so deflation is less likely, and inflation is more likely. Interest rates are more volatile. History is informative but not gospel.
For a professional view of future stock and bond returns (at least intermediate term), visit Research Affiliates (my favorite), or JP Morgan or Schwab .
Click below to go to the calculator.