The Dangerous Illusion of Average Returns
How erroneous statistics are misleading everyone
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TL;DR
We're all told to trust the "average rate of return" for our long-term investments, but this common wisdom is built on a dangerous illusion. The financial industry's use of "rolling averages" is statistically flawed, resulting in decades-long periods where positive average returns masked zero or negative real returns. You'll discover why your actual, real-world return is lower than the simple average about 75% of the time and, most importantly, learn how to build a financial strategy based on certainty, not arbitrary numbers.
“This is fine…”
One of the main talking points of conventional financial wisdom is the idea of investing for the long term to get "average" rates of return. The premise is that if you just stay in the market, investing in things like the S&P 500, you’ll be fine. Even when the markets go down, if you “stay disciplined,” keep your money in, and keep investing, we’re told the average return will be significant—maybe 8%, 10%, or even 12% (depending on who you talk to)—and you’ll end up with a nice amount of money when you retire.
For decades, people have been taught to invest in low-cost index funds, and that as long as they stay with it, everything will turn out okay. But there are significant problems with this approach that most people are just unaware of.
Today, I want to demonstrate that the logic behind this idea of average rates of return is not only statistically flawed, but also, practically speaking, potentially dangerous to your financial future.
The Statistical Error with Averages
First, let's talk about the math. A lot of times, what people do when they analyze the market is look at a "rolling 30-year average." They’ll take a 30-year period, say 1930 to 1959, and get the average return. Then they’ll take the next period, from 1931 to 1960, and calculate the average return. The same for 1932 to 1961, and so on. If you do this from the start of the S&P 500 to the present, you currently get 66 30-year periods. These periods are then averaged, and we now have a sort of average of averages. This gives the illusion that we have a significant amount of data to pull from to create a reliable average market return.
The crazy thing is we all know we’re not supposed to use past performance to determine future market returns; it's literally printed on every investment statement you get. But, even so, that’s exactly what’s happening. All the different types of analyses, like Monte Carlo simulations and others, which sound very scientific, do exactly this. They just look at the past, jumble it all together in an average, and tell you that’s what you can expect.
But even putting that logic problem aside, there’s a bigger statistical error everyone is falling for. Let me explain with an analogy that I learned from Dr. David Babbel’s great work on this subject.
Imagine you have 30 people in a room, and you get their average weight. Then, you swap out just one person and recalculate the average. It's easy to see that swapping out one person isn't going to significantly change the average weight in the room, because you’ve shared 29 out of 30 data points from the previous average.
This is exactly what financial models do. The 30-year period from 1931 to 1960, for example, shares 29 of the same years with the 1930-1959 period. This is a statistical problem called autocorrelation, or overlapping samples. The data isn't independent; it's almost identical.
So, here’s a reality check: In the last 95 years of S&P 500 market history, we don't have 66 different 30-year experiences. We have three. Three non-overlapping 30-year periods. If we wanted to examine an entire “financial life,” from working years through retirement, that would span more like 60-70 years. In that case, the market history we have so far with the S&P would provide us with only a single data point!
To get the data we think we are getting from a “rolling” 30-year average, we’d need thirty 30-year periods, or 900 years of market history. We don't have nearly enough data to provide any statistical relevance.
The Real-World Consequences
This isn't a theoretical problem. These statistical errors have real-world consequences. I'm talking about significant periods of time where we've had no growth from a real return perspective.
When you look at averages, you’re just taking the arithmetic average of the percentage numbers. That has nothing to do with what happens to your money. The one exception is if you start with a pot of money and never add to it or take from it. In that case, the actual return will be the average return. But, in most cases, people are accumulating or spending. So money is going in and/or out of the investment. Every time you add or subtract money, it changes the outcome, and the average no longer applies.
Let’s look at an 11-year period from 1998 to 2008.
If you take the simple average of the S&P 500 with dividends, it was +3%.
But the actual return an investor got, after accounting for their annual contributions, was -2.7%.
I’m obviously cherry-picking a time frame here. The point is not really about highlighting the negative return; it’s about the fact that it’s possible to have a positive average return and still lose money. I don’t think many people realize this. The other point to consider is that most investors in this scenario will think they’re earning 12% because that’s what they were told the average is.
Think about that. For a decade—a third of your career—you might be expecting to have $350,000 saved after investing $20K for 10 years, but you end up with $175,000 (less than what you put in!).
If this happened in the first 10 years of your career, for the next 20 years, you’d need a real annual return of almost 15% to make up for lost time and get the money you thought you’d get over 30 years with a 12% average return.
(Side note: I moved to San Francisco and got my first job in tech in 1998 - so this is what I experienced)
This isn’t a one-time event:
1929-1939 (11 years): A nearly +5% average return, but the actual return was basically zero, a little less than -1%.
1955-1974 (20 years): The average return was +4.7%, but the actual return was 0.2%. Zero growth.
1962-1974 (13 years): The average return was +2.5%, but the actual return was -0.5%. Zero growth.
1998-2008 (11 years): The average return was +3.2%, but the actual return was -2.7%.
Averages can, and do, lie. And they can lie for a long time.
The S&P 500 with dividends has had seven 10-yr+ periods with a positive average return but a negative or zero actual return
The S&P 500 without dividends has had 24 of these periods, the longest being 20 years.
Quickly: I want to recognize that I’m cherry-picking data here. But it’s real data, and these periods have happened to people. So, while I wouldn’t say fear-mongering (nor exuberance) over cherry-picked data should be a best practice, ignoring these real possibilities is not wise.
Actual Returns Are Less Than the Average 75% of the Time
Going back to those rolling 30-year averages, there’s another pretty wild trend. When I analyzed the returns on those 30-year periods, I discovered that the actual return, the real growth on your money, is lower than the average return about 75% of the time.
My analysis here suffers from the same overlapping data problem I mentioned earlier. However, I’m bringing it up to demonstrate that, even when we use the conventional methodology, the data shows that the average return they promise is not what investors actually get the vast majority of the time. People are planning their lives according to these averages, but even when playing by the industry's own rules, they only come out ahead 25% of the time.
The Other Side of Dollar-Cost Averaging
We're often told about the positive effects of dollar-cost averaging—the idea that when markets go down, you keep buying shares at a lower cost, which improves your return when the market recovers. And that's true, it's a good thing.
But what's never discussed is the other side of that coin. If you're investing for the long term, you're also buying shares when they're at all-time highs. If you're dollar-cost averaging for three down years out of ten, you are doing the opposite for the other seven years. You're buying shares when prices are higher, and when the market goes down, that actually decreases your return on that side of the equation.
By the way, isn’t the #1 of investing to “buy low, sell high?” By that rule, shouldn’t we buy all of our stocks like we do when we dollar-cost-agerage instead of only 3 out of 10 years? 🤷🏻♂️
At the end of the day, many of these ideas are rationalizations to make people get comfortable with the significant risk they're taking when investing in the market.
So, What Should We Do?
I’m not saying it's bad to invest in the stock market. I’m only saying we should be more honest about the risk. Everything's great when the markets go up, but it really, really matters what's going on in your life when they go down. Are you in a job that could be affected? Will you have to liquidate investments just to live? What if you're retiring and need to withdraw money from your retirement fund during a down market?
The big problem is that most of us have our entire financial future tied to this system. We're just passively hoping that our 30 years won't be one of the bad ones.
Instead of trying to make the risky market be something that it's not, I suggest this: keep investing in the market, but have some part of your financial life that truly is safe. Build a financial foundation first, in a system that's entirely in your control, with assets that provide liquidity and certainty and are completely uncorrelated from the market. Then, once you have that foundation built, you can afford to take some risk without having to restart your entire financial life if something goes wrong.
At StackedLife.com, we teach strategies that combine whole life insurance—an asset class with liquidity and guarantees—with private wealth strategies to build a platform of liquidity, certainty, and growth. We can help you get massively improved outcomes with safety and control, so you can take advantage of the change that is always coming, rather than react to it.
I’m John Perrings, an Authorized Infinite Banking Practitioner and founder of StackedLife. Instead of taking high risk to get a high return, we help our clients implement strategies that create multiple safe returns with the same money repeatedly.
I’ve implemented IBC for hundreds of clients and educated thousands more via my podcast, articles, and courses at StackedLife.com.
Want to work with me? Schedule a free consultation here.