I’ve been wondering about the merits of so-called “Buffered” Exchange Traded Funds (ETFs) for some time now. Buffered ETFs, or “Defined Outcome” ETFs, were first offered by Innovator Capital Management in 2018. I tend to avoid posting about new investment products because they seem to come and go at a dizzying pace. And there’s usually very little historical data to evaluate the likely risks and returns for these new products.
But Buffered ETFs have been around for nearly five years now and are growing in popularity. Since 2020, total investments in Buffered ETFs grew from $300 million to about $10 billion today, a more than 30-fold increase.
What Are Buffered ETFs?
The most common type of Buffered ETFs offer returns that mimic a well-known stock index like the S&P 500, but by using derivatives such as options, they moderate the severity of any losses. But there’s a catch. In return for this downside protection on index investing, these ETFs also have an upside “cap”, where returns cannot exceed a set value, no matter how high the underlying index goes. Buffered ETFs essentially shave off the extreme highs and lows of normal stock index funds.
This graph from Charles Schwab illustrates one example of a Buffered ETF with a 5% downside buffer and a 15% upside cap.
So, in this case, the ETF loses 0% when the index loses anything from 0 to -5% in value. For any index losses greater than 5%, the ETF shaves 5% off of those losses. So, an index loss of say, 20% is moderated to a 15% loss for the ETF. For the upside, the ETF provides the full positive return of the index up to 15%. If the index return is say, 25%, then the ETF returns 15%.
The percentage returns noted here apply over a set period. By far the most common period is one year. So, in most cases, you can think of these buffers and caps in terms of annual returns.
There are myriad types of Buffered ETFs involving a wide range of stock indices as well as varying amounts and styles of downside protection and upside cap. ETF Database lists more than a hundred buffered ETFs, and I suspect the entire universe of such ETFs is even larger.
Rather than investigating all these Buffered ETFs, today I’ll focus on some of the most common and uncomplicated ones. So, here are similar graphs showing the setup of three popular Innovator Buffered ETFs that are based on the S&P 500.
The downside buffers for each ETF are defined above the graphs (9%, 15%, and 30%, respectively). The upside caps are defined at the time the ETF is issued. According to Innovator’s website, the current starting upside caps for these three ETFs, from left to right, were 25%, 19%, and 16%, respectively. The stronger the downside buffer, the weaker the potential upside returns, which is consistent with the investing maxim that lowering risks always results in lower potential returns.
It’s also worth noting that many Buffered ETFs, including the three examples above, are issued on a monthly basis. So, if you buy a Buffered ETF that starts in January, the downside buffers and upside caps apply to a year running from the start of January to the last day in December. This means that if you buy a January Buffered ETF in July, the downside buffer, upside risks, and final returns you receive will vary from the ETF’s description.
How Have Buffered ETFs Performed?
Although Buffered ETFs haven’t been around very long, it’s worth examining their young life so far. When looking at investments that offer some purported advantage over a more passive approach, it’s helpful to compare their risks and returns to a super simple index fund. That’s because long-term investing in low-cost broad market index funds has been shown time and again to be the most mindful investing approach.
So, in the rest of this post, I’ll make comparisons between Buffered ETFs and their underlying index. Note that this is not a “benchmark” comparison, which determines whether an actively managed ETF can “beat” a more passive approach. After all, these ETFs are purposefully designed to perform differently, not necessarily better than, an index. In this case, comparisons to the index reveal the risk and return tradeoffs of using a Buffered ETF instead of a simpler index fund.
The oldest Buffered ETF I could find was the Innovator series shown in the graph above, which appears to have started in 2018. The ticker symbols for the January version of these funds are BJAN, PJAN, and UJAN. I looked these funds up in Portfolio Visualizer, but it only returned data through January 2020. Nonetheless, I thought it would still be interesting to see how these three Buffered ETFs (all based on the S&P 500) have performed in comparison to the S&P500 during this time.
Here are three graphs from Portfolio Visualizer showing the performance of a $10,000 investment in BJAN, PJAN, and UJAN (red line) as compared to the SPY (an index fund for the S&P 500; blue line). First, here’s the graph for BJAN (which has a 9% downside buffer and a roughly 25% upside cap).
And here’s the graph for PJAN, which has a 15% downside buffer and a roughly 19% upside cap.
And here’s the graph for UJAN, which has a 30% downside buffer and a roughly 16% upside cap.
And here is a table comparing some key statistics for the three Buffered ETFs as well as SPY.
| ETF | Final Value | CAGR | St. Dev. | Max. Drawdown |
| BJAN | $ 12,082 | 5.99% | 14.75% | -16.85% |
| PJAN | $ 11,694 | 4.93% | 10.78% | -11.81% |
| UJAN | $ 11,180 | 3.49% | 6.97% | -7.97% |
| SPY | $ 13,401 | 9.43% | 20.65% | -23.93% |
All three of the Buffered ETFs suffered a smaller maximum drawdown than SPY. And for that fleeting comfort, these funds returned Compound Annual Growth Rates (CAGR) of approximately 1.5% to 6% less than SPY.
Leveraging The Data
There’s an adage that if you want to win any argument in investing, just pick a different historical timeframe. Consequently, we shouldn’t read too much into this one brief period of comparison. For example, if you had bought PJAN at the start of 2022, you’d have a graph that looks like this.
Your investment in PJAN would have handily outperformed SPY for 16 months straight and counting. In this case, the CAGR for PJAN was -0.14% as compared to -9.77% for SPY. I can see why Buffered ETFs have grown so much in popularity in the last couple of years.
So, the big question is how likely is it that the Buffered ETF investor will get a pretty lousy outcome like the first period (Jan 2020 to present) versus a much better outcome like the second period (Jan 2022 to present)? Given that the buffers and caps in the ETFs I’ve presented in this post are all set up on an annual return basis, I applied the annual return buffers and cap rules to historical annual return data for the S&P 500 going back to 1928.
We’ve seen that PJAN typically provides an outcome mid-way between BJAN and UJAN. So, to simplify the analysis, I confined my theoretical historical calculations to just PJAN. I calculated the theoretical rolling 5-year and 10-year annualized returns for PJAN for all investing periods from 1928 to the present. I picked 5 and 10-year periods because permanent loss risk analysis suggests that 5 years is probably the shortest prudent duration to invest in stocks. Historically, for the S&P 500, the chance of losing inflation-adjusted (real) money on stocks over a 5-year investing period is only around 25%. And if you buy and hold stocks for 10 years, the chances of a loss are more like 10% to 13%.
Here’s a graph of the rolling 5-year nominal annualized returns for PJAN (theoretical) versus the S&P 500 going back to 1928.
In almost every 5-year period the S&P 500 investor would have obtained superior nominal annualized returns than the theoretical PJAN investor. When talking about long-term risks, inflation-adjusted (real) returns are often more relevant, so here’s the same graph on an inflation-adjusted basis.
You’ll note that the gap (or difference) over time between the S&P 500 and PJAN returns on an inflation-adjusted basis is nearly identical to the gap on a nominal basis. (This makes sense for reasons that I won’t get into here.) So, from this point forward I will just stick to inflation-adjusted returns to simplify the discussion.
Here’s the same graph for inflation-adjusted (real) 10-year rolling annualized returns.
Over a 10-year period, the outperformance gap for the S&P 500 can get quite large when the stock market is doing well. Conversely, when the stock market is doing poorly there’s usually a relatively narrow gap between S&P 500 and PJAN performance.
We can better see the gap between the performance of the two investments if we plot differences between the theoretical PJAN and S&P 500 performances as shown in this graph for rolling 5-year returns. Orange bars indicate 5-year periods when PJAN theoretically outperformed the S&P 500, and the blue bars show the opposite situation.
It turns out that there were only a few periods in history where theoretical investment in PJAN would have provided better 5-year results than simply investing in the S&P 500. Those periods were pretty scary including the Great Depression in the 1930s and the Great Financial Crisis starting around 2008. And PJAN would have theoretically outperformed by something like 5% annualized during these times, although not necessarily making money in each case. But interestingly, PJAN wouldn’t have outperformed particularly well during the bursting of the Dotcom Bubble after 2000.
Here’s the same inflation-adjusted difference graph but on a rolling 10-year basis.
Over a 10-year investing period, PJAN would have theoretically outperformed during the same times of crises that we’ve already seen. However, a longer investing period reduces PJAN’s advantage during these crisis times, outperforming the S&P 500 by only about 1% to 2.5%.
So, how often should we expect such stock market crises when PJAN would perform best? Here are the chances of losing inflation-adjusted money in either investment since 1928.
| ETF | 5-Year | 10-Year |
| PJAN | 19.78% | 15.12% |
| SPY | 24.18% | 12.79% |
Over a 5-year investment period, historical data suggest that PJAN would reduce the chances of losing money by about 4%. Put another way, there were 22 historical 5-year periods where the S&P 500 lost money, but only 18 periods where PJAN would have theoretically lost money (a difference of 4 periods).
And interestingly, the theoretical chances of losing real money with PJAN over a 10-year period were about 2% higher than for the S&P 500. This is because there were to two 10-year periods when PJAN real returns were slightly negative while the S&P 500 returns were slightly positive.
Conclusions
For long-term investors (5 to 10-year range) there appear to be few advantages to Buffered ETFs, at least for the specific ETFs I evaluated here. The most likely outcome is that you will lose out on a significant amount of easily obtainable returns. And the chances that you will make money (positive return) with a Buffered ETF while the index does not (negative return) are quite low.
And I haven’t even raised the issue of costs. For example, the expense ratio of PJAN is 0.79%, while the expense ratio of SPY is 0.09%. So, if you have $100,000 invested, you will be paying the PJAN fund operators $790 per year, as compared to paying $90 per year for SPY. And these costs compound quickly over a long-term investing timeframe like 10 years. To make it simple, let’s assume the stock market is stagnant for 10 years and your investment value stays right at $100K. Over those 10 years, you will have paid $7900 to PJAN versus $900 to SPY¹.
Buffered ETFs appear to be just another example of how the finance industry tries to extract more money from investors by appealing to their fear of short-term paper losses. This conclusion is very similar to my past evaluations of other products that appeal to the investor’s fear of routine volatility including Low-Volatility ETFs, Tactical Asset Allocation funds, and Target Date Funds. And given the billions of dollars invested in Buffered ETFs in the last couple of years, I expect that the finance industry will continue to pump out even more sparkly new products that attempt to tame the “scary” stock market.
1 – Note that fund costs are figured into all the Portfolio Visualizer graphs in this post, but are not figured into my calculations of theoretical PJAN historical performance. In that sense, my calculations benefit PJAN in these index comparisons. And even without costs included, PJAN’s outcomes were usually quite poor as compared to a similar index fund investment.