Captain James T. Kirk: What worries me is the easy way his counterpart fit into that other universe. I always thought Spock was a bit of a pirate at heart.
Mr. Spock: Indeed, gentlemen. May I point out that I had an opportunity to observe your counterparts here quite closely. They were brutal, savage, unprincipled, uncivilized, treacherous–in every way splendid examples of homo sapiens, the very flower of humanity. I found them quite refreshing.
Captain James T. Kirk [to McCoy]: I’m not sure, but I think we’ve been insulted.
—Star Trek, “Mirror, Mirror” (1967)
As any sci-fi nerd who reads this can likely attest, “Mirror, Mirror” is one of the best known Star Trek episodes. It’s an Alternate Universe story, with the all-too-common “transporter malfunction” serving as catalyst (aside: if transporter tech is invented in my lifetime I will never, ever use it). In the Mirror Universe, the Federation is instead the Terran Empire. Imagine all the worst impulses of the Roman emperors, applied on a galactic scale.
In Terran society, only the strong survive. Don’t like your boss? Kill him. You simply take what you want through violent force. Women. Resources. Power. It’s pure Social Darwinism.
A fairly horrifying way to organize social and economic activity, when you really stop and think about it. Imagine being tortured in the Agonizer Booth every month you underperform the S&P 500. Many of us would be on intimate terms with the Agonizer Booth by now.
But as Mr. Spock observes at the end of the episode, the Terrans are just an exaggerated expression of basic human nature. The kinder, gentler humans of the Federation share the same basic impulses. They have the same capacity for cruelty and violence.
They’re us. We’re them.
It’s the same in our relationships with our investment managers. Many of their failings, real and imagined, reflect our own weaknesses and failings, both as individuals and allocators.
Why are there so many overly diversified, low tracking error portfolios out there? The dominant methods allocators use to evaluate performance incentivize the construction of overly diversified, low tracking error portfolios.
Why do so many bottom-up managers dabble in macro tourism? Allocators have unrealistic expectations for how true bottom-up portfolios should perform during broad market selloffs.
Why does it feel like so little money is managed with an emphasis on “real world” cash flow generation by “real world” businesses? Because the dominant models for asset allocation are based on abstracted baskets of securities.
Why is does it feel like so much money is managed in a short-term, overfitted fashion? Clients want 200% upside capture and 0% downside capture, and they want it “consistently.”
Our flaws and biases as allocators manifest themselves in our managers’ portfolios. They’re amplified by the intense pressure that comes with managing other people’s money. We end up in a kind of nightmarish feedback loop. The more pressure a manager is under during a period of underperformance, the worse that feedback loop gets. The more exaggerated our flaws and biases become as they’re translated into security selection and portfolio construction.
sometimes often laugh at the silly conversations I have with capital intro people and third party marketers. They’ll say things like: “Fund X was actually up in December 2018! You should really take a look.” As if that, on its own, is somehow a meaningful data point.
But I shouldn’t laugh.
I shouldn’t laugh because I made them this way. Me, and others in seats like mine. Ultimate responsibility for the pervasive absurdity in the investment management business lies with us. We not only tolerate it, but actively encourage it. We encourage it with our peer group rankings and tracking error parameters and quarterly performance evaluations, not to mention our fear and greed.
I’ve always loved Wes Gray’s take on this, using a poker metaphor:
On the other side of the table is an institutional poker player, hired by wealthy investors, to play poker as best as possible. This poker player is a pure genius, mathematically calculates all probabilities in her head, and knows her odds better than anyone. Now imagine that our super player, as a hired gun, has a few limits. “We need you to maintain good diversification across low numbers and high numbers. We also want to see a sector rotation between spades, aces, and clubs. Don’t take on too much risk with straights and flushes, stick to pairs like the market does…” No one would ever play poker like this. But in finance, this is how people play.
They’re us. We’re them.