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.

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[Special thanks to longtime reader, Matthew Morrison for reviewing this post and providing some key input.]

Practically since stock markets were invented, people have looked for ways to avoid the inevitable periodic dips in stock prices.  Such attempts combine the unmindful concept of trying to beat the market, which I posted about last time, with the equally unmindful concept of trying to time the market.  For reasons I’ve noted before, a mindful approach to investing suggests that successful short-term market timing is impossible with any consistency.

Nonetheless, people have created myriad systems that attempt to successfully time the market.  The idea of day trading alone covers a vast array of potential market timing systems, signals, and economic indicators for individual stocks, bonds, funds, and just about every possible asset.  So, unlike my last post on beating the market, I’m not going to attempt to review multiple market timing systems.

Instead, I’m going to focus on one category of market timing that goes by the snazzy name of “Tactical Asset Allocation”(TAA).  Essentially, TAA uses valuation, economic, momentum, sentiment, and/or other indicators to shift portfolio allocations among two or more asset classes over time.  The goal is to favor assets that are expected to perform well in the future and avoid assets that are expected to perform poorly.  TAA shifts can involve anything from slight refinements in allocation percentages to all-or-nothing bets on particular assets.

Given the poor track record of trading and market timing, you might be surprised that I’m even addressing TAA here at Mindfully Investing.  But after doing a bit of research, I found some pretty reasonable arguments for (and against) TAA that amount to more than mere conjecture and self-interested cheerleading.

The Dream

The idea of TAA grew out of basic market-timing research dating back to at least the 1970s.  At first, the premise was simple; find the best times to buy and sell stocks.  But as finance researchers, including luminaries like Robert Shiller and Kenneth French, found ever more ways to potentially predict future asset returns, it caused a seemingly inevitable progression toward the more nuanced idea of TAA.  By the 1990s, tens of billions of dollars were already invested in TAA mutual funds of one type or another.  And yet, even today, the debate still rages on the best timing indicators, the best assets to include, and even whether any of the many flavors of TAA work.

TAA has been tried with many different potential indicators, timing systems, and combinations of assets.  So, I thought it makes sense to start with a select example that became popular in the last cycle of peak TAA interest, which perhaps predictably, occurred in the years around the 2008 financial crisis.

Moving Averages – Meb Faber published a paper in 2007 and updated it in 2013 that reviewed a simple TAA system using the 200-day moving average (MA) of stock prices.  Faber’s paper generated so much interest that at one point it was the most downloaded publication on the SSRN website.  The next year, Jeremy Siegle issued the fifth updated edition of his best-selling book Stocks for The Long Run, which added an analysis of a very similar 200-day MA system.  Faber stresses that he didn’t invent the 200-day MA idea.  It’s been around for a long time, which makes me wonder why his paper caused such a fuss.

Faber’s version of the 200-day MA system shifts to all-cash investments (3-month T-bills) when the monthly stock price falls below the 200-day MA and back to stocks when prices rise above the same MA.  Here’s a graph from Faber’s paper showing the growth of a $100 initial investment in the S&P 500 using the 200-day MA system (labeled “timing”) as compared to buying and holding the same basket of stocks.

The timing system outperformed buying-and-holding the S&P 500 in terms of both annualized absolute and risk-adjusted returns over this period.

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Way back in 2016 I wrote a series of articles about “Beating The Market”, where I said right up front, “If you were hoping these articles discuss methods for beating the market, then you can stop reading.”

Instead, those articles summarized mountains of behavioral and market data indicating that beating the market with any consistency is essentially impossible.  Nonetheless, I occasionally find myself dwelling on the unmindful question of how one might attempt the seemingly impossible feat of beating the market, which is today’s fuzzy topic.

Background

Beating the market is the notion that an investor can achieve higher returns than a broad market index (a benchmark) that is relevant to their investing style.  So, a U.S. stock picker might compare their performance to the S&P 500 Index, while a U.S. bond picker might compare their performance to the Bloomberg U.S. Aggregate Float Adjusted Bond Index.

Funds that try to beat the market are often referred to as “active” funds.  The fund managers sift opportunities and, through some form of professional judgment, try to select a subset of opportunities that they hope will outperform a relevant benchmark.

So-called index funds take a very different approach by eliminating judgment almost entirely.  Index fund managers simply mimic the investments in an index that is built upon rigid rules.  The use of such index funds is sometimes referred to as “passive” investing but I think that rather convenient dichotomy is misleading.

I recently reviewed an annual study of “active” fund managers’ ability to beat their benchmarks.  Unsurprisingly, the track record of professional stock and bond pickers is still just as dismal as it ever was, with only about 10% of active funds beating their benchmarks over a decade or more.  And when measured against their active fund peers, only 1% of such funds can stay in the top performance quartile for five years running.

Some Hypotheses

So, it would seem futile to consider ways to beat the market.  Even so, I’ve run across some intriguing beat-the-market hypotheses over the years.  Some of these hypotheses appear stronger than others, and all of them are subject to data constraints and implementation uncertainties.  But to me, none of them seem entirely proven yet.

1. Be A Math Genius

A few years ago someone pointed out to me that Renaissance Technologies’ Medallion Fund, started by mathematician Jim Simons in 1988, has an utterly amazing long-term record of beating the market.  Here are a few amazing stats for the fund from 1988 to 2018:

• Never produced a negative annual return in 31 years
• A compound annual return of 63%
• $100 invested in 1988 would have grown to $398.7 million!¹

By comparison, $100 invested in the S&P 500 over the same period would have garnered a paltry $1,910!

The exact tactics producing these results are closely guarded secrets.  The Medallion Fund appears to hold thousands of short-term positions at any given time.  It’s alleged that Medallion bets correctly on these positions only 50.75% of the time.  But when compounded over millions of such positions, that slight edge produces huge dollar margins.

Do you want some?  Well, you can’t have it.  The Medallion Fund is only open to current and former employees of Renaissance Technologies.  Given that Renaissance’s publically available funds don’t perform nearly as well, it appears that the Medallion Fund has severe size constraints.  If it was open to the public, it would be flooded with new money and the strategy would likely stop working.

So, the market can be beaten, but the vast majority of us don’t have the smarts to do it.

2. Pick A Better Fund Manager

Given that the Medallion Fund proves there is an exception to the rule, it seems logical that other exceptions might exist.  I already noted that about 10% of active funds beat their benchmarks over periods of one to two decades.  So, why not just pick one of those funds and beat the market that way?

The problem is the second observation that only 1% of active funds have consistently superior performance.  In other words, if you pick one of the funds that beat their benchmark for the last decade, chances are they will fail to continue that success in the next year, much less the next decade.

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Over the years I’ve boiled down mindful investing into one sentence:

• Buy and hold for the long-term (10 years or more) a moderately diversified set of low-cost stock index funds.

That’s it.  And even though there’s a lot of evidence, analysis, critique, and philosophy to be found in the over 400,000 words I’ve published at Mindfully Investing, when it comes to action items, this one sentence sums it up pretty well.

Of course, if you take a mindful approach to investing, and life in general, you also know that you shouldn’t simply accept anything as true without conducting your own rational assessment.  So, for those who want to dive deeper, I can break down this sentence into three explanations with supporting evidence provided at these Mindfully Investing links:

1. Buy and hold stock funds for the long-term, because historical data indicate that the chances of losing inflation-adjusted money in broad stock funds after about 10 years are very low, while the same is not true of bonds or cash.
2. Moderately diversify stock fund holdings, because no one can consistently predict the future and it’s unwise to put all your eggs in one basket.
3. Use low-cost index funds, because picking individual stocks or trying to “beat the market” are losers’ games.

Regarding the third point, it’s been quite a while since I’ve written about the folly of trying to beat the market.  So, I thought it would be a good time to review and update evidence regarding the performance of so-called “active funds”, where professional managers try to pick a set of stocks in hopes of outperforming a market index or benchmark.  The most common examples of such market indices are the S&P 500 and the Dow Jones Industrial Average.  But there are hundreds of other indices that can be used as appropriate comparisons to almost any style of active fund management.

Scorecards and Barometers

Fortunately, it’s not very hard to track the performance of active fund managers because at least two organizations collect and publically report on active fund performance on a semi-annual basis.  The first such report is called the SPIVA Scorecard and is produced by S&P Dow Jones Indices.  The second report is called the Active/Passive Barometer and is produced by Morningstar.

Given these reports come out shortly after the beginning and mid-points of each year, I was originally thinking I’d wait to write about them until after the New Year.  But on the other hand, I’ve been reviewing these reports for many years, and the overall story changes very little with each new report.  So, I can almost guarantee that what I’m about to tell you will be fully supported by the next set of reports in early 2022.

Annual Performance

An easy way to start sifting through the stacks of data in these reports is to consider how active funds perform on an annual basis.  Here are two graphs showing the percentage of active stock funds that have underperformed their benchmarks for every year presented in the SPIVA and Morningstar reports for U.S. stock funds and global stock funds, respectively.

In a good year, 40% of actively managed stock funds underperform their benchmarks.  And in a bad year, as much as 85% of these funds underperform.  That’s certainly not a thrilling performance in either case.  But an investor might be able to pick an active fund that has about a coin flip’s chance of outperforming a similar index fund in the next full year.  So, it might seem like the returns of an active fund could outpace the returns of a similar index fund over the long term, assuming that the active fund avoids catastrophically underperforming in any given year.

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Wait don’t go!  This post is not about GameStop and Robinhood!  But I have to admit that they appear in today’s post as bit players.

I’ve been slowly researching the relationship between investing and gambling over the last few months.  When I started that research, nobody was predicting anything like the GameStop-Robinhood-WallStreetBets-AMC-Nokia-SilverSqueeze-etc. turmoil.  (Let’s just call it the “GameStop fiasco” for short.)  But in hindsight, there were clear warning signs months, and even years, ago that something like this could explode on the markets.  But before we read the warning signs, I want to address a more fundamental question.

Is Investing Just a Form of Gambling?

I was dismayed to find that when I searched for the word “gambling”, Google told me that people who searched for “gambling” also often searched for the word “investment”.  But perhaps that’s not so surprising if you consider the similarities between the two.  In both cases, you place some money on a desired outcome, like the white horse will win or the price of Stock A will go up, and you can either gain or lose money.  And in both cases, you have no control over an uncertain outcome.  So, what’s the difference?

The Britannica website defines gambling as:

• The betting or staking of something of value, with consciousness of risk and hope of gain, on the outcome of a game, a contest, or an uncertain event whose result may be determined by chance or accident or have an unexpected result…[my emphasis]

Put another way, gambling involves high levels of uncertainty.   In contrast, I’ve advocated here at Mindfully Investing that, when done properly, investing is nearly certain to be successful.

Uncertainties of Gambling vs. Investing

At the casino, the odds depend on the game and whether you know how to play it well.  The best odds you can get at a casino are about a 51% chance of losing (or a 49% chance of success).  And most casino games offer higher chances of losing.  Even with sports betting, the odds are set such that you have more than a 51% chance of losing, assuming that you can’t know more about the outcome of a sports contest than the person making the odds.¹

So, what are the odds of losing money when investing?  Just like gambling, the answer depends on the particulars.  I’ve written before about the chances of losing money in stocks based on historical data.  This graph shows the chances of losing money in stocks on an inflation-adjusted basis over different holding periods using historical data from the S&P 500 going back to 1928.

History suggests that there’s a 13% to 17% chance of losing inflation-adjusted money when holding stocks between about 7 and 12 years.  And if data going back to 1871 are included, these chances decrease a bit more.  So, I’ve previously summarized these estimates as a roughly 10% chance of a loss over 10 years of stock investing.  And notably, the chances of a loss after 18 years of stock investing is zero, if history is any guide.

What about bonds?  Here’s the same graph for investing in the 10-year U.S. Treasury bond.

It might surprise you that the chances of losing money with “super-safe” bonds don’t decline over time and are generally higher than the chances of losing money with stocks.  But recall that 1) bond returns are typically lower than stock returns and 2) this graph presents chances of a loss on an inflation-adjusted basis.  In other words, 10-year bond returns have often failed to keep pace with the rate of inflation.  Nonetheless, the chances of a loss with bonds hover around 35%, which is still better than the odds you’ll ever be offered at any casino.

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