You can track shifting asset class and/or strategy allocations over several years for a long list of asset managers, and then add it all up to arrive at a data-driven industry trend. Easier said than done. This is an extremely heavy lift without the aid of a database that has already aggregated such information – if at all. But, we think there is another way to generate such a signal that yields a similar conclusion (if you know how to read the tea leaves). Hint: As always, it still comes down to the people…
That preamble aside for the moment, we will spare you the geek-speak and give you the cart before the horse: In the exhibit below, based on US Securities and Exchange Commission Form ADV data for 181 large asset managers (w/ AUM >$10 billion) over the 5 years ending March 2017, Alphacution’s newest analytic – assets under management per employee, or AUM/e – indicates, upon calculation of total weighted average AUM/e for all reporting funds per period, that strategy trade durations have been lengthening. Translation: On average, asset managers (including hedge funds) have been increasing their allocations to asset classes like private equity / private markets and real estate. Now, in the past, we have attributed increasing AUM/e largely to improvements in process efficiency, agility, or a theme we have been highlighting lately – operational alpha. However, while increasing AUM/e is a solid proxy for increases in productivity as long as we know that the underlying business strategy remains unchanged, changes to the underlying strategy can be the primary cause of increasing AUM/e. With the data presented above yielding an absolute 5-year increase in total weighted average AUM/e of 24.6% (from $187.5 million to $233.7 million), we would be reluctant to attribute anything more than a portion of this increase to improving process efficiencies (because harvesting production efficiencies is usually difficult, slow and incremental).
Also, our reading of these tea leaves – re: strategy migration towards private markets / real estate and away from listed (equity / debt) markets – may be obvious to many, but how we arrived at this reading is arguably unique. Here’s some backstory:
First explored in a post from December 2016, the summary of Alphacution’s hypothesis on this score is this: There is a relatively predictable relationship between headcount, assets under management and trading / investment strategy.So, like Pythagoras – and his famous theorem – if you know 2 of these variables (ie – headcount, AUM, strategy), you can calculate (or guess) the third – or at least that’s how our hypothesis is currently framed.
This relationship exists because each strategy has capacity limitations that, when tested or violated, degrade anticipated performance. (It’s the liquidity, stupid!) Moreover, this (theoretical) strategy capacity is related to native holding period – or, turnover frequency (ToF). In short, higher/faster ToF yields lower capacity; lower/slower ToF yields higher capacity. For example, high-turnover quant strategies should emit relatively low AUM/e and low-turnover private equity strategies should display high AUM/e.
We will stop here with this appetizer for now. Our upcoming asset manager study will flesh out the details of these concepts – and introduce Alphacution’s techno-operational benchmarking framework. Yes, it’s a mouthful – but, once we add technology spending (per employee) to the mix of key variables (in a follow-on study for the Fall 2017), we expect the estimation and prediction capability of this new framework to be quite valuable.