ETF Review: ASYMmetric S&P500 (ASPY)

Today I will review the ASYMmetric S&P500 ETF, ticker ASPY, in an unconventional way.

I still remember when I listened to the very first episode of the Animal Spirit podcast because I was on holiday in Costa Rica, traveling by bus from the capital to a surf spot on the Pacific. It was also one of the last holidays I and my wife had as a couple, or I should say one of our last holidays full stop (thank you kiddos).

At the time my reaction was “really, another podcast?”. I think I had already lined up Tuesday for Invest Like The Best, Thursday for Meb Faber (or it was Wednesday?), and Friday for Masters in Business. Three podcasts a week was already the max I could handle…I thought.

Too bad Apple Podcasts do not offer stats (or maybe they do and I do not know where to look), my guess is I currently spend at least 7 hours/week listening to podcasts. If you consider that I do not do it while I work, because I cannot handle English content when I am (semi)concentrated doing something else, and I do not commute anymore, that’s the very max I can devote to it. But I love it.

Anyway, back to Animal Spirit.

At first, I loved their Talk Your Book spin-off because…that’s what I would do if I was them and partially what I do here: talk about new investments I find interesting. But it is really hard to match new, interesting and legit investment products with a weekly schedule. However hard you search, there might not be 52 opportunities every year (let’s say 48 considering they have repeated guests); I feel they are leaning towards “less scrutiny-more consistency in the schedule” than the reverse. And I do not think you need me to mention the conflict of interest of getting sponsored by the show guests.

This week (if I manage to finish this post on time), they hosted Darren Schuringa, CEO and Founder of ASYMmetric ETFs. In 2021, Darren launched the ASPY ETF: the ASYMshares ASYMmetric S&P500 ETF is an exchange traded fund that employs a passive management investment approach designed to track a quantitative long/short hedging strategy that seeks to generate positive returns in bear markets and capture the majority of the upside of a bull market [from Bloomberg]. It is a rule-based strategy that can go long a minimum-volatility basket of stocks within the S&P500 or short the index. The signals that govern the strategy are two:

• a trend signal that checks if the price of the S&P500 is above or below the 200-day simple moving average
• a risk/volatility signal that checks the dispersion of return of the stocks within the index

According to Darren, ASPY tries to earn 75% of the S&P500 returns when the index goes up and a positive 25% when it goes down (since it can go short). As for other rule-based strategy ETFs, the sponsor provides an “index” that mimics the strategy in the past, even if the ETF wasn’t trading yet:

9.24% vs 6.60%? Imagine if Darren was not looking to leave “some upside on the table”! 😉 Even if you take out 0.9% as an annual fee, returns are impressive. Let’s look now at the performance since the launch:

Neck to neck; but this graph does not include dividends: with dividends, the S&P500 returned 8.56% while ASPY was 6.39% over the entire period.

I really like the idea behind the product, applying a trend sleeve to a broad equity index to control drawdowns and risk. Just a few days prior to the podcast, I landed on this post about trend following:

Even if the underlying stocks behave randomly, it seems trend following on an index may have mathematical merit. If an index is trending up or down, then it is likely its correlation and internal weighting support that trend. If neither of those change, then the “trend” of the portfolio should probably continue.

Now to me, I wouldn’t trend follow based solely on price alone. I think it makes more sense to monitor standard deviation and internal correlation of the index, try and derive where the index’s geometric return is in its process, and then bail on the trend when the standard deviation, correlation and price say the trend is over.

Well, this is (almost exactly) ASPY! Unfortunately, the ETF is quite young: all the right premises are there but is past performance a good indication of what will happen in the future? If anything, the Animal Spirit interview pulled me into the ‘do not touch this’ camp. Here is a list of all the red flags I found:

RED FLAGS

Darren’s Past

“I run a 5-star mutual fund, I was behind one of the largest HF seeds in the US” but…none of those mutual fund and hedge fund experiences are on LinkedIn? His first listed job experience is as the founder of Yorkville Capital: “Yorkville offers its clients exclusive access to some of Wall Street’s most talented money managers and the ability to invest alongside them without sacrificing the security and comfort of having their assets held by a large financial institution“. A sort of asset management consultant / fund of funds manager. During the show, he painted himself as THE guy who found the strategy while his professional experience was more in finding other guys that were good at creating returns. Why I checked? Because if you have a successful HF earning 2-and-20 in fees, you do not go into the retail space. If you move, is to close the shop and become a Family Office.

Just saying that how he presented himself on the show, conveying success to push for the strategy, it is not what you get looking at LinkedIn…and the reason might be that LinkedIn is public (if you want to), so harder to lie there.

Mixing Tail Hedging strategies with Trend

In previous posts about TheItalianLeatherSofa model portfolio, I describe what is a tail hedging strategy and a trend strategy; in particular, why they work in different market environments, linking resource material from AQR. Yes, Tail Hedging did not work in 2022. Does it mean it is useless? I do not think so, that is my opinion. But comparing your trend strategy, an apple, with tail, an orange, is not fair, at best.

Also, 2022 was clearly not a bad year for trend.

The Bad Environment

During the show, Ben Carlson describes really well the worst scenario for trend strategies. “Exactly last year” is not the correct answer: scroll back at the third graph in this post, the market whipsawed up and down but it rarely triggered the fund to shift from ‘neutral’ to ‘long’. Last year, the S&P500 traded above the 200ma at month end only in March and November: in both cases ASPY ended up losing money. In November, the S&P500 traded above the 200MA only at month end, which should have triggered ASPY to go long, then went down for all of December, signaling ASPY to sell, only to rally back in January. This is what Ben refers to as the worst scenario, in at the top and out at the bottom. The fact that it did happen for a month in 2022 does not mean the whole year was ‘a potential disaster’.

Not Backtested but Forwardtested

“VIX is bad to give trading signals”, dispersion is better. Well Sir, how did you get to that conclusion, if not testing those rules with past data (which is, drumrolls, the definition of backtesting)? The fact that your strategy’s rules, which you “magically” created in 2021, worked in the past does not mean you forward-tested them (but kudos for the marketing spin), you just do not want to admit you (potentially) gold seek them.

The Four Quadrants

“We simplified in a different fashion, for investors. We use a traffic light analogy”. Wut? Ok, this is just marketing gibberish but it is really weird the way he put it. Do you think investors in the Medallion fund care if they understand the strategy or not? What should drive the strategy is…what makes money. Typically, trend strategies are just on/off (either long/short or long/flat) but if your plan works best with 3, 4 or 5 states, then go for it. That “simplified” is a bit worrying.

Rule Based

Execution is really important for trend strategies. Here you potentially have a strategy than can be easily front-run? Maybe it is just me, the S&P500 has such liquidity that this risk might not be there…

But I do not understand why they are rebalancing at month’s end like everyone else. Why do not rebalance at another date or, even better, diversify your rebalance strategy?

ZSPY

He explained quite badly how they manage to get the investor the 2x return that matches the period return. I think what they do is that they periodically rebalance between the 90% of the fund that is invested in the S&P500 and the 10% invested in futures. In simple terms, if at the end of the day, market went up, they sell futures / buy index. The rebalancing mechanism is what allows to match periodic returns. TQQQ, to pick a levered ETF, is only invested in futures so there is no chance to ‘reset the leverage’ by rebalancing.

The 60/40 Comparison

Sure 2022 was a terrible year for 60/40. But it was a good year for trend. Actually, the first good year since many many bad ones. And ASPY is, again, a trend strategy. Do you remember those dudes that wanted to beat Michael Jordan by playing golf just so they could claim they beat Michael Jordan? Do not be that dude.

Darren also compares a couple of times ASPY full 2022 result, -10%, with the S&P500 LOW of 2022, -24%. The S&P500 closed 2022 at -18%. Again, details but…

It is not Complicated but it is Elegant

That is the Holy Grail of trend strategies; actually, of every trading strategy. I have been there, looking for it, I know. But it is very very hard to find, usually because the biggest drawdown is the one you didn’t experience yet. That’s why “stock-market-like returns with low volatility” are so hard to experience in the real, not backtested, world.

End

I really like the idea behind ASPY (and ZSPY too). I love the message about capital preservation, reducing drawdowns and volatility, to compound faster. It is also hard to imagine a scenario when this ETF generates a big loss; the worst that can happen is to heavily underperform the S&P but still gain. A DIY version of the strategy that goes long SPY if it is above its 200MA and moves to cash otherwise generated 5.5%/year since 2007 (cannot test longer than that because BIL, the ‘cash like ETF’, was launched in 2007). If the backtest is reasonable, you spend 1% in fees to get back (hopefully) 3% of additional returns per year via the dispersion filter (compared to the DIY scenario).

I am just worried when someone presents the ETF with such enthusiasm and no caution. I understand it is not the best tactic to sell, but if the product proves itself, customers will arrive: that’s the only sure thing in finance. If you generate high returns with low vol, eventually people will throw money at you like women at a Chippendale show (the Disney+ series is great, watch it).

What I am reading now:

Follow me on Twitter @nprotasoni