Charts with Chartolini: Statistically Speaking, This Is the Best Year Ever for ETFs

ETFs have been utilized more in 2020 than any other year, ever. Investors have sought out the vehicle’s flexibility in order to position portfolios during a very tumultuous period. If we adopt an analytical baseball mindset, we can find support for the “best year ever” claim—even if ETF flows don’t break any records in 2020.

ETF fund flows garner a lot of attention (as they should!) since they show investment dollars into or out of a particular strategy and can be helpful in deciphering investor positioning and sentiment. They’re also just fun to talk about—one of the reasons I write a monthly flows commentary. In reality, however, they are a derivative of other activity that may not be as visible or reflected in a fund – as well as the asset managers business bottom line for that matter.  

Beyond the market approaching the final quarter of the year – and the last time ETFs can garner flows in 2020 – the Major League Baseball playoffs are now underway. As a result, the game seeped into my subconscious[1] while doing my daily research, and I realized that ETF fund flows are actually analogous to wins for a starting pitcher: fun to discuss, easy to point to, but obfuscate overall performance.

Wins and flows: A performance mirage

Wins are a visible, headline-grabbing statistic used since the dawn of baseball to measure a pitcher’s effectiveness and performance. However, wins are an outcome-based statistic affected by a plethora of other variables beyond the pitcher’s control, including offensive run support, defensive skill level and park effects (i.e. play in a bandbox[2] or a field that is the size of canyon). Regardless of that nuance, wins are relied upon because players, coaches, general managers and talent scouts have used the statistic for years. Yet, using only wins to judge a player can lead to the wrong conclusion about the performance of a player in a given year.

For example, consider the win-loss record for two real players below. Using just this data point, Player B may be selected as having the better year, and perhaps that’s right, but more analysis is needed.

Player A: Wins – 10, Losses – 9

Player B: Wins – 18, Losses – 6

While wins are still quoted, their importance has diminished as a result of the rise of advanced statistics that provide the ability to better isolate skill from luck (i.e. SABRmetrics).[3] – metrics such as ERA+[4], FIP[5], and WAR.[6] When in-depth analytical lenses that strip away luck aspects not within a pitcher’s control are used, Player A becomes the choice.

BIG REVEAL: Player A is Jacob deGrom and Player B is Jon Lester, and deGrom won the 2018 Cy Young award while Lester finished ninth in the award voting.[7]

Our reliance on wins to gauge performance is a heuristic borne out of tradition—no different than research analysts utilizing fund flows to gauge the performance of a fund or industry in a particular year. Fund flow statistics trace all the way back to the first type of pooled vehicle (mutual funds), and were used back then to dissect their investment trends and business results. Unlike mutual funds, ETF investment and usage can show up in more data points beyond what we see in the headline flow figure. As a result, like wins, flows shouldn’t be the sole statistic used to judge performance or effectiveness in a given year.

More data required

To understand if ETFs are having a great year, we need to look beyond the headline data points—much like the ballot voters did for deGrom in 2018. These deeper data points are signaling that ETFs are having their best year ever in terms of usage, even if fund flows fall short of the 2017 record of $461 billion.

As it stands right now, ETFs have taken in $310 billion during 2020. Adding in the historical fourth-quarter average figure ($87 billion), we see 2020 likely falling short of the full-year record. But that’s ok: The peripheral statistics – like FIP for a pitcher – indicate that investors have gravitated towards ETFs more in 2020 than any other year.

ETFs can be bought on the secondary market, sold short and accessed through derivative contracts, like options. These actions create an ETF’s peripheral statistics and reflect a vast ecosystem of users. While some of those activities may result in fund flows, not all of them do. For instance, there may be enough supply of shares in the secondary market to meet the specific investment demand, negating the need to create or redeem shares in the primary market and interact with the fund (i.e., recording a flow).

In order to get these peripheral statistics to quantify the number of users trading in the secondary market or structuring a sophisticated trade through arbitrage or derivatives, we gathered the numbers on all 2,000-plus ETFs over the last 10 years—a vast amount of data points.

When we broaden the scope of ETF analysis beyond flows, we see that 2020 has broken, or is poised to break, records for:

• Secondary market volumes – The year-to-date figure of $24.6 trillion outpaces the full-year 2018 record by $50 billion, with three months left to go. The average fourth quarter trading volume over the last 10 years is $4.6 trillion, so a $30 trillion volume mark is likely
• Number of trades - There have been over 1.4 billion ETF trades executed so far in 2020, outpacing the 2018 figure by 400 million trades in just nine months.
• Options volumes - At 1.8 billion, total contract volume on options tied to ETFs is within 40 million of the 2018 record. Volumes are on target to beat the record even if next quarter comes in at the lowest fourth-quarter mark of the last 10 years (257 million contracts in 2009).
• Short interest - The high-water mark for short interest on ETFs in 2020 reached a record notional of $252 billion.[8] 

The chart below shows year-to-date 2020 figures for these four variables compared to the prior max level and the long-term average. ETFs 2020 is Pedro Martinez 2000-esquse – a year in which Pedro had his lowest wins total in three years (sort of like not having the most flows) but posted a staggering 291 ERA+ (ranks first in the modern era of baseball).

Source: Bloomberg Finance L.P. as of 09/23/2020. Calculations by SPDR Americas Research.

Raise the banner

In a year of unimaginable pain, suffering and loss, there is a need to seek out areas of positivity. In my view, ETF usage is one such area that we can celebrate. 2020 flows may not break records, but we must realize that flows aren’t the only way investors interact with ETFs—much like the reality that not every aspect of a game’s outcome is in a pitcher’s control.

The advanced statistics above illustrate how investors have gravitated towards the ETF structure more in 2020 than any other year. And yes, there are three more months to go in this “season,” but trade figures and volumes can’t be negative, so it’s not too early to raise the banner and claim 2020 as the best year ever for ETFs.

[1] I am a big fan of America’s pastime, even though my beloved Red Sox are in the cellar this year because they traded one of the best players in baseball

[2] A bandbox is a slang term designating a small ballpark in which it is easy to hit home runs

[3] The empirical analysis of baseball, especially baseball statistics that measure in-game activity.

[4] ERA-Plus adjusts a pitcher's earned run average (ERA) according to the pitcher's ballpark (in case the ballpark favors batters or pitchers) and the ERA of the pitcher's league

[5] Fielding Independent Pitching is a statistic that estimates a pitcher’s run prevention independent of the performance of their defense. . FIP is based on outcomes that do involve defense; strikeouts, walks, hit by pitches, and home runs.

[6] Wins Above Replacement is a non-standardized baseball statistic developed to sum up "a player's total contributions to his team. . It is the number of additional wins the players team has achieved above the number of expected team wins if that player were substituted with a replacement-level player: a player who may be added to the team for minimal cost and effort.

[7] While deGrom only one 10 games because he played on an anemic Mets team he posted a 9.9 WAR with a 218 ERA+, the latter of which ranks 20th all-time for single season since 1880. 

[8] Based on the sum product of each individual ETFs highest level of short interest multiplied by the price of the ETF for every year since 2014, per Bloomberg Finance L.P. as of 09/23/2020 per calculations by SPDR Americas Research

Glossary:

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