AI is Kicking My Ass...
AI is Kicking My Ass...
A review of AI-powered stock portfolios vs Humans
The Deload explores my curiosities and experiments across AI, finance, and philosophy. If you haven’t subscribed, join nearly 2,000 readers:
Disclaimer. The Deload is a collection of my personal thoughts and ideas. My views here do not constitute investment advice. Content on the site is for educational purposes. The site does not represent the views of Deepwater Asset Management. I may reference companies in which Deepwater has an investment. See Deepwater’s full disclosures here.
Additionally, any Intelligent Alpha strategies referred to in writings on The Deload represent strategies tracked as indexes or private test portfolios that are not investable in either case. References to these strategies is for educational purposes as I explore how AI acts as an investor.
AI > Humans
Charlie Munger loved the analogy of the one-legged man in an ass-kicking contest. He used the analogy often to describe people who fail to learn basic knowledge to be good at their profession. Since most people don’t spend much time learning, they’re destined to get a beat down.
One of my favorites from Munger:
“If you’re going to live a long time, you have to keep learning. What you formerly knew is not enough. If you don’t adapt, you’re like a one-legged man in an ass-kicking contest.”
Being a good investor demands a life-long approach to learning. Markets change. Opportunities change. Even the tools we use to invest change, with AI coming to be the biggest change to markets yet.
AI is like a 50-legged man in an ass kicking contest. Two legged humans don’t stand a chance to beat AI at investing, nonetheless a one-legged one. I know because I’ve been testing it.
I have half a year of data about Intelligent Alpha now, my system for using generative AI to challenge markets. Results remain great. More than 75% of all the strategies I track are ahead their benchmarks since inception. My average core strategy is +4.2% vs respective benchmarks, and the median strategy is +2.7%.
But Intelligent Alpha doesn’t just aim to outperform indexes. It also aims to be better than humans in direct competition. I’ve been testing three such direct competitions:
The IA Large Tech Focus vs a Pure AI version. It’s a concentrated portfolio of 12 large cap tech stocks that aims to challenge the QQQ, and it’s +16.7% vs the ETF since inception. The strategy combines human intelligence with Intelligent Alpha. My AI committee picks the stocks that can go into the portfolio, and their votes determine weighting, but I decide when the committee should review portfolio and have final approval over new stock additions. I’ve also tested a version of the Large Tech Focus strategy where I have no input other than prompting, so it’s purely the output of my AI committee.
IA Human Comp A (I’m using this name to keep the underlying fund anonymous). The underlying fund is a growth-focused strategy managed by a team of humans with a long-term track record. I use a representative universe of stocks from the strategy for my AI committee, allowing it to pick and weight the AI-powered version of the portfolio.
IA Human Comp B. The underlying fund is a value-focused strategy managed by a team of humans with a long-term track record. I use the portfolio of stocks from the underlying fund as the universe for my AI committee, allowing it to pick and weight the AI-powered version of the portfolio.
In every case, AI is outperforming humans since inception, and by a decent amount too.
Why? Is AI’s dominance sustainable? My thoughts…
Data > Feelings
The biggest advantage AI found vs the humans in every strategy was embracing mega cap tech and semiconductors. In both of the growth and value strategy comps, AI went heavy into GOOGL, META, AMD, and semi cap names like LRCX and AMAT.
AI favored the tech names to insurance companies (BRK and DHR), banks (JPM), and medtech (MDT) in the value fund. It favored tech to retail and consumer names (FIVE, ALGN, ETSY, SQ) in the growth fund. While many of those companies are high quality, few of them come with the growth of the tech names, and in some cases their multiples are even higher.
In the Large Tech Focus strategy, my AI committee universally loved NVDA, making it a 16% conviction position in the pure AI version of the strategy. In the human version of the strategy where I add my supposed intelligence, I bumped NVDA out of the portfolio because it felt too hot. That difference represents a significant part of the pure AI’s alpha vs my human-edited version.
While humans are stuck thinking about how the megas just enjoyed an incredible rally in 2023 and how it can’t possibly happen again, AI only looks at the qualitative and fundamental realities of those big stocks. And the truth?
The mega caps aren’t that expensive.
Before I even pulled the mega cap valuation data, I generally knew that the mega were trading around 30x forward FCF. I knew that meant the group was yielding around 3% vs the 10-year Treasury at ~4%. I knew that it’s hard to say that the mega cap group is “super expensive” in that context. Is it really that crazy for the best companies in the world to yield 3% while growing earnings mid-teens while the 10-year hovers around 4%?
But that’s AI’s undying advantage.
Even as I knew all of the valuation realities of tech, I’m still hesitant to add more mega cap exposure because [caveman voice] “price move too fast.” AI doesn’t suffer such first level thoughts. It just puts strong investments in its portfolios. No over thinking.
Death of the Middle
Chris Dixon of A16Z described a concept called the “Death of the Middle” on David Perell’s podcast. The Death of the Middle is how the Internet pushes everything to the edges. In retail, that means either Amazon or LVMH. Macy’s is dead. He predicts AI will have a similar effect on many other industries.
I think the human-managed investment industry will suffer the Death of the Middle. Human public equity managers will survive either with a big brand name or a truly unique, exotic strategy. AI will eat up everything else in the mediocre middle.
The brand name manager adds value through prestige, and assets are still allocated by humans after all. In that same Dixon interview, he noted that humans like humans, giving the example that humans still watch other humans play chess. They don’t watch robots play chess even though they’re better at it. The same will hold true for famous asset managers. At least for a while.
Truly exotic ideas, ones that AI couldn’t conceive on its own, should also draw assets provided they show consistent returns. The challenge with exotic managers will be preventing an AI clone that does it better. Today’s experiment review shows AI can already take a human-driven investment strategy and do it better.
Don’t Over Think It
I recently said that the mega cap stocks need a breather. NVDA and META can’t keep going up 40% a month forever as a matter of logic. The idea of a breather doesn’t interfere with the idea that mega cap tech isn’t as egregiously expensive as bears argue. A pullback is a short-term sentiment and positioning call. Fundamental valuation is relevant longer-term. At least that’s how my simple human mind justifies the existence of both ideas.
Even if my view to wait on vertical moves like NVDA is right, I’m not sure how much alpha to the Large Tech Focus strategy I’ll add by waiting, missing the rally on the way up, and hoping I’m daring enough to pull the trigger when these stocks are down 5-10%. Probably not enough alpha to replace what I’ve missed by not listening to AI so far.