Titling up this month with a straightforward play off Forrest Gump's "Stupid Is is As Stupid Does" line.
From what we have seen, not much difference in the world of active management, especially amongst "quant"-oriented managers. Over the years, many quant funds were sending us their monthly results and now, most of those have gone belly up. So, the point here is to give you a sense of what can and can't work in systematic investing based on our relatively extensive experience.
Most of what we will talk about is products that go down the quant path with monikers of Factor-driven/Smart Beta, Artificial Intelligence, and Machine Learning. Most of this is here to stay in investment management. If you go through our iAWR Blog, you will see reviews of such products with a priori (yes, that's theoretical deduction) prognostications of whether such products will deliver. Invariably, we generally concluded that they would not.
So, let's review:
AQR QSPIX - 2019 YTD -5.43% against 2018's -12.35%; over-engineered, factor-based nonsense priced at a whopping 2.32% with $2.7B (down from $3.3B) of institutional investor money. This one is likely going to require a hit on the Reset button. AQR even suggests that the comparison index is 3 month T Bills! Which also raised an eye with us in our original review--anyone seen US Treasury bills dump 18%? Not sure what the institutions that make up the majority of the $30B+ at AQR see in any of this!
AIEQ - As the trading symbol suggests, AI using IBM Watson supplied information. Basically sub-performed SP500 on an inception-to-date basis. It had a preponderance of AMZN for a while that explained some outperformance but that went away quickly as FANG stocks died. At 0.77% per year, apparently complete waste of money if one desires alpha. This came out of the gate with $70M in assets, hit $150M and now down to $117M, it will likely be back to double digits soon unless the issuer figures out that there is limited "Intelligence" in the "AI" moniker.
SPLV - bias of money to the "low volatility" (LV) sectors, so you get a bias to stocks that do better in lower interest rate environments (including market shocks) until rates go up on a sustained basis, but overall there is little alpha here to argue on its behalf versus the SP500 over longer timeframes. At 0.25%/year, relatively cheap but with limited room for alpha long-term, what's the point? $11B in investor money thinks otherwise!
VQT/PHDG - both symbols are active plays on a rules-based approach to move money between SP500 long-exposure, a VIX volatility hedge and cash. Introduced right after S&P came up with the "optimal" allocation rules that worked during the 2008/2009 period but, of course, had no chance of surviving thereafter. VQT had several hundred million in it and now is lucky to have $17M! At 0.39%, very expensive given the sheer lack of return relative to the SP500.
KOIN/BLOK - This one is probably the most interesting out of all of these updates. You may not know that both symbols are geared to investing in blockchain-related technologies. In our review of their underlying processes, KOIN uses some form of "AI" for security allocation while BLOK is humans trying to make educated bets. So, we picked KOIN (when intro-ed in early 2018) over BLOK and the results speak for themselves. At 0.95%, it looks expensive until you see it outperformed the SP500 by over 2% since inception and blows away BLOK by a healthy margin, both net of that big fee. Now, that is a systematic process doing its job! And, with only $10M in assets vs BLOK at $110M, no surprise that generally no one gets it.
So, how do we know the answer a priori? Simple:
1) The stock market is efficient so use listed stock prices for analysis (there is very limited to no secret money-making information anymore in liquid/developed markets). Any investment strategy that strays from this basic idea is likely doomed (AIEQ and most active mutual funds are trying to argue otherwise);
2) Investing in liquid stocks and then sitting on them for long periods of time is a sure way to bleed alpha over time (applies to the majority of mutual funds and ETFs); and
3) Any rules-based process will struggle as more money invests in the rule and the rules-based alpha gets eroded (clearly VQT/PHDG/SPLV's issue).
There is more to our analytical lens as it relates to return distributions but that will likely glaze your eyes so we will save that for another day or contact us directly for a lively discussion.
All three of these simple dictums are mathematically provable too. Note that annual fund cost has nothing to do with the above analytical points and is just a panacea that marketers can use to drive simple but potentially misplaced investment decisions.
So, get more selective, understand systematic investing and how to capitalize of it for your investing future. And, if you have a great pick, by all means, send it over as we are always on the hunt!
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