How Does AI Perform in Volatile Markets?
How Does AI Perform in Volatile Markets?
Hint: It does well by doing less
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.
Good Products are Time Machines
Save me money, make me money, or save me time.
We all want more money and more time. Since money is stored time, what we all really want is more time.
Because time is scarce and precious, people are willing to pay for it, so building products around time is the surest way for a company to earn customers. All great products save us time in some way. The ability of great products to save us time makes them timeless.
Investment products may be the ultimate time saver. Great investment products are time machines that compound with the effect of saving more time over time. Nothing gives you more time than a great long-term investment.
The foundational belief of Intelligent Alpha is that AI will make investors more money than indexes and human managers in the long run. AI will win against indexes and humans because it fixes their flaws as investors. AI is unemotional unlike humans, and it’s capable of adding intelligence to structure unlike an index. That makes AI the ultimate investment time machine.
Despite my confidence in AI’s investment prowess, it’s not going to win every day or every week vs benchmarks. AI as a mechanism to make more money from investments is a time machine built on patience, as are all great investment products. The key with patient investment is that you don’t blow up along the journey, and it’s no different for AI.
How AI Acts in Volatility
“AI will get killed in a bear market.”
That’s a common concern I hear about Intelligent Alpha. The suspected frailty of algorithms and machines in market turmoil is fueled by past blow ups. LTCM collapsed legendarily in 1998, its models succumbing to massive leverage (250-1) when the market worked against it. The “Quant Quake” of 2007 levied pain on the entire model-driven quantitative finance sector as popular factor trades unwound. While the Quant Quake didn’t result in any explosive failures like LTCM, it highlighted the crowding that can happen in model-driven investment strategies.
Will we have future market turmoil caused by machines? Probably. Will Intelligent Alpha strategies be excessively harmed? Anything’s possible, but I doubt it.
Most Intelligent Alpha’s strategies don’t actively trade and don’t use leverage, eliminating two of the major issues for LTCM and the Quant Quake. That doesn’t mean my AI-powered strategies would survive unscathed; however, the strategies are built to play the investment game within an index-like structure + machine intelligence, so I suspect it’s unlikely that Intelligent Alpha would be down much more than representative benchmarks in times of turmoil.
Data is always a more powerful tool to convince than anecdote or logic. While we’re not in a bear market or serious period of market stress, we endured some solid market volatility over the past two weeks that gives us a window into how AI-powered portfolios might do in tougher market environments.
Perhaps unsurprisingly, anywhere tech was a focus, Intelligent Alpha portfolios were challenged vs benchmarks during the mid-April tech sell off. During the toughest week for tech, here’s what Intelligent Alpha’s performance looked like vs benchmarks:
The 12-stock Large Tech Focus strategy holds large positions in NVDA, MU, TSLA, and TSM, all stocks that suffered in the tech sell off two weeks ago. As a result, the strategy lost 450 bps of relative outperformance vs the QQQ during the tech sell off. The AI Average, which focuses on AI stocks, also lost ground to the QQQ. The less concentrated 30-stock Tech Select portfolio lost only 40 bps of ground to the QQQ. While the relative underperformance in the tech correction is disappointing, each of the Intelligent Alpha strategies maintains a healthy lead vs its benchmark.
We should expect portfolios focused on tech will have some level of incremental stress, I don’t know that the performance of the tech portfolios tell us much. The results in the cap strategies are more interesting.
The Large Cap Core portfolio, which is my direct competitor to the SPY, gained some modest ground vs the benchmark. The Large Cap Core has consistently been underweight tech since July 2023 inception, and it’s exceeded the toughest index in the world by 270 bps over that time despite tech’s huge contribution to the SPY’s performance.
The Large Cap Core Equal lost a bit of ground to the RSP ironically because the AI-powered portfolio has a bit more big tech exposure. Despite the tech turmoil, the Core Equal maintained a 750 bps lead on its benchmark since inception. Interestingly and before the tech sell off, my AI investment committee updated the Core Equal portfolio with just two conviction weightings where all three members of my AI committee nominated the stock: UNH and CI.
Finally, the Asymmetric Upside strategy did its job by adding 150 bps vs the SPY. It’s a large cap strategy that aims to pick stocks that have 2x upside vs downside potential. When everything is going up, that strategy should keep pace with its benchmark. When everything is going down, the strategy should outperform. In the end, that’s the point of every Intelligent Alpha strategy — to play within the rules of some investment game and try to create a persistent advantage vs its benchmark. The market turmoil shows that the strategies do that for better and worse.
Don’t Just Do Something, Stand There
Toward the beginning of Intelligent Alpha, I wrote about Charlie Munger’s legendary advice that investors should sit on their ass more. Do less.
Much of the insight from investment greats like Buffett and Munger comes from their understanding of human nature, not some unique perspective on finance. Great investors teach themselves to manage the many mistakes we humans are prone to make given our emotional nature. One way to avoid such mistakes is to just do nothing. Doing nothing isn’t always the answer, but it’s a good answer more often than most would allow themselves to believe.
Part of the reason indexing works is because it does nothing provided you leave it alone. AI can do the same. You can program AI to do nothing. The best part is that AI can do nothing with intelligence. It puts thought into its portfolios. Indexes just follow rules without intelligence. They do nothing, period.
As markets stabilized, Intelligent Alpha strategies did too by doing nothing. Those that lost ground largely gained it back. Those that gained ground largely held onto it.
It’s a small sample, so these are generalizations, but when you’re early to a new paradigm, everything is a small sample. Every new experience can only be a generalization. As we keep gathering more data and experience investing with AI, our conclusions can grow stronger. In the interim, the recent volatility and the performance of our AI strategies tell me that Intelligent Alpha probably won’t suffer excessively in times of stress, just as the structure intends.
If Intelligent Alpha can consistently deliver on generating excess returns over other investment products without blowing up, AI will prove to be a time machine for investors.
