The Adventure
People are motivated by different things in life. Some by money. Some by power. Some by impact. I’ve always been motivated by adventure.
A good adventure leads to some discovery about the world or yourself. A good adventure requires some risk because there’s nothing to be discovered in comfort. Some of the best adventures sneak up on you. You don’t even know you’re on an adventure until you’re right in the middle of it.
Intelligent Alpha has been one of those sneaky adventures for me. A year ago, I started an experiment to see if ChatGPT could build stock portfolios to compete with the S&P 5001. That experiment turned into an artificial intelligence-powered investment committee of three large-language models that now oversee dozens of strategies.
I’ve been silent on the adventure of building Intelligent Alpha for the past couple of months because we’ve been working on a big announcement:
Intelligent Alpha is bringing modern AI-powered investing to the market.
Last week, we launched our first product, the Intelligent Livermore ETF (LIVR), which uses our AI investment committee to identify opportunities inspired by the world’s greatest investors and traders. The Livermore ETF allows the committee to invest in stocks across different geographies, themes, and sectors with the current portfolio focused on AI, Asia, Latin America, and defensive stocks.
James Dyson said the key to creating a breakthrough product is difference for the sake of it. That applies just as well to investment funds just as it does to vacuum cleaners. New managers need to do something unique to get the attention of investors, and then they need to perform well to keep their trust. We built our first product to be purposefully unique — a sort of mini multi-manager fund that mixes the perspectives of several investing greats.
We’re different. Now we need to perform.
AI’s Superpower: Lack of Emotion
The Intelligent Livermore ETF gets its namesake from Jesse Livermore, the first great Wall Street trader. Livermore was the subject of the famous book Reminiscences of a Stock Operator written in 1923 which details the lessons he learned as a trader. Many investors still view the book as canon 100 years later.
One of Livermore’s great insights was:
“There is nothing new on Wall Street or in stock speculation. What has happened in the past will happen again, and again, and again. This is because human nature does not change, and it is human emotion, solidly built into human nature, that always gets in the way of human intelligence. Of this I am sure.”
My year-long experiment in investing with Large Language Models taught me that AI’s clearest advantage is lack of emotion. There’s nothing broken in the human-centric investment process except that it’s performed by emotional humans. We feel pressure and doubt our judgment when stocks are down. We feel joy and ascribe undeserved genius when our stocks are up. Emotion doesn’t get in the way of artificial intelligence, and that advantage vs humans is permanent.
Jesse Livermore himself is a reminder of this fact.
Livermore made and lost many fortunes in the market. Despite his vast knowledge about managing emotions as an investor, his career ended in ruin. Livermore’s namesake serves not just as a nod to our pioneering introduction of AI-powered investment strategies but also a reminder that no matter how many lessons we learn, it’s the continual application of those lessons that will determine our longevity and success.
Livermore is just the first product powered by Intelligent Alpha’s AI investment committee. We have so much more to come.
Replication vs Inspiration
Intelligent Alpha is the first asset manager built to use modern large-language AI models to do investment selection. The frontier is always interesting, and we’ve been lucky to have a lot of interest in Intelligent Alpha. Being on the frontier also means we’re responsible for educating the market about AI-powered investing.
Some who follow Intelligent Alpha have characterized us as “replicating” existing managers like Buffett, Druckenmiller, and others, but I see it differently. We inspire our AI to think like great investors, not replicate them.
To replicate is to copy someone. Portfolio replication of great managers has been around for a long time. Look at a 13f, buy the same stocks, and make changes when the next 13f hits. You just need a web browser and a brokerage account, not AI.
Some research even suggests that pure replication can be a viable strategy, although to the extent replication outperforms the actual managers seems more an unpredictable accident than a persistent feature.
We don’t try to replicate great managers. We use great managers as a basis for our AI Investment Committee to develop an investment philosophy and select on its own merits.
Just as the young value investor might study Buffett and Klarman and Grantham for inspiration to form a philosophy, we do the same with AI. We infuse our investment committee with the wisdom of great investors, then let AI apply that wisdom as it sees fit. Sometimes that means an Intelligent Alpha portfolio will overlap with a human manager who served as inspiration, sometimes it might not.
The reason we use great managers as inspiration is because LLMs allow AI to “think” in abstract ways like a human manager that wasn’t possible before with traditional machine learning techniques. We don’t just reduce a manager down to his favored quantitative factors and a list from a 13f. We try to have the AI understand the kinds of companies and ideas a manager favors from a qualitative lens too, and I believe the combination of the qualitative and quantitative is what will set investing with modern AI apart from prior AI investing efforts.
Ideally, just as Warren Buffett learned more techniques and vastly outperformed his mentor in Benjamin Graham, we want our AI committee to evolve continually as an investor with the goal of being better than the managers that inspire it. With the right continued evolution of our process and the advancement of AI models, the odds should favor AI being a better investor over time than its many legendary mentors.
Move Fast
In a technology-driven business, Elon Musk said it best: “Moats2 are lame.”
Other firms will find ways to use LLMs in their investment process, and the only way to stay ahead is pace of innovation. Look at Google. Bing has been 97% (my estimate) as good as Google for a long time, but it doesn’t matter. Google has maintained its 3% edge by being fast innovators. They’ve stayed ahead, they’ve kept customers happy which builds trust in a brand, and ultimately that is the strongest moat.
A former Googler, Paul Buchheit, makes winning in tech clear: “If you're in the lead, and you're moving faster than everyone else, then no one can ever catch up.”
We promise to keep moving fast to create new, innovative techniques that improve our AI investment committee and launch new products that empower AI as an investor. That’s why we believe that the future of investing is intelligent.
Important Information:
1. S&P 500: S&P500: It is an unmanaged index of 500 common stocks primarily traded on the New York Stock Exchange, weighted by market capitalization. Index performance includes the reinvestment of dividends and capital gains.
2. Economic moat refers to a business's ability to maintain competitive advantages over its competitors in order to protect its long-term profits and market share.
Investors should consider the investment objectives, risks, charges and expenses carefully before investing. For a Prospectus or Summary Prospectus with this and other information about the Fund, please call +1-215-469-1717 or visit our website at iaetfs.com. Read the prospectus or summary prospectus carefully before investing.
Investments involve risk. Principal loss is possible. Redemptions are limited and often commissions are charged on each trade. Unlike mutual funds, ETFs may trade at a premium or discount to their net asset value.
High Portfolio Turnover Risk. The Fund’s investment strategy is expected to result in higher turnover rates. This may increase each Fund’s brokerage commission costs, which could negatively impact the performance of a Fund. Rapid portfolio turnover also exposes shareholders to a higher current realization of short-term capital gains, distributions of which would generally be taxed to you as ordinary income and thus cause you to pay higher taxes.
Leveraged, Inverse, and Inverse-Leveraged ETF Risk. Leveraged, inverse, and inverse-leveraged ETFs expose the Fund to all of the risks that traditional ETFs present (see “Underlying Fund Risks” above). Leveraged ETFs seek to provide investment results that match a multiple of the performance of an underlying index (e.g., three times the performance). Inverse ETFs seek to provide investment results that match a negative (i.e., the opposite) of the performance of an underlying index.
Foreign Investment Risk. Returns on investments in foreign securities could be more volatile than, or trail the returns on, investments in U.S. securities.
Small- and Mid-Capitalization Companies Risk. Investing in securities of small- and medium- capitalization companies involves greater risk than customarily is associated with investing in larger, more established companies. These companies’ securities may be more volatile and less liquid than those of more established companies.
Large-Capitalization Companies Risk. Large-capitalization companies may trail the returns of the overall stock market. Large-capitalization stocks tend to go through cycles of doing better – or worse – than the stock market in general. These periods have, in the past, lasted for as long as several years.
AI Model Risk. The Fund is actively managed using the AI Models, the output of which is heavily dependent on multiple inputs, including current and historical data (collectively, “Data”). To the extent the AI Models do not perform as designed or as intended, the Fund may not be able to achieve its investment objective and may lose value.
Machine Learning Risk. The Fund relies on publicly available “machine learning” selection processes as well as data and information supplied by third parties that are utilized in those processes. To the extent the machine learning process does not perform as designed or as intended, the Fund’s strategy may not be successfully implemented, and the Fund may lose value. If the input data is incorrect or incomplete, any decisions made in reliance thereon may lead to the inclusion or exclusion of securities that would have been excluded or included had the data been correct and complete.
Risks Related to the Use of Form 13F Data. The Form 13F filings used to analyze trading trends are filed up to 45 days after the end of each calendar quarter. Therefore, a given investor may have already sold some or all its positions by the time the AI Models evaluate the filing. Furthermore, the Form 13F filing may only disclose a subset of a particular investor’s holdings, as not all securities are required to be reported on the Form 13F. As a result, the Form 13F may not provide a complete picture of the holdings of a given investor. An investor may hold long positions for a number of reasons, and the AI Models may not appreciate the reasons, or the strategies followed by an investor who makes the filings. The analysis of the AI Models may not be representative of the investor’s universe or the strategies that give rise to the reported holdings. Because the Form 13F filing is publicly available information, it is possible that other investors are also monitoring these filings and investing accordingly. This may result in inflation of the share price of securities in which the Fund invests.
New Fund Risk. The Fund is a recently organized investment company with no operating history. As a result, prospective investors have no track record or history on which to base their investment decision. There can be no assurance that the Fund will grow to or maintain an economically viable size.
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Information presented by Intelligent Alpha LLC and Deepwater Asset Management, both SEC-registered investment advisers. Registration does not imply any level of knowledge or skill. For more information and important disclosures, please see our FormADV 2A brochures which are available at www.intelligentalpha.co and www.deepwatermgmt.com. The Fund is distributed by Quasar Distributors, LLC. The Fund’s investment advisor is Empowered Funds, LLC which is doing business as ETF Architect.
Hey, Doug!
I was ecstatic when I saw the news about your launch of LIVR, because it should have been me))! Seriously, congratulations on this historic event, LIVR is up 8% in less than a month, amazing results, especially the maximum allocation (at the moment) in PDD - it was a stroke of genius to buy it on the 30% drawdown after the earnings report, ahead of the rally in Chinese stocks.
The thing is, I've experimented with paper trading during earnings season with ChatGPT and got some interesting results, please, check them out here - https://www.reddit.com/r/EarningsWhisper/comments/1fcpqhd/trading_during_earnings_season_with_chatgpt/, maybe Artificial Investors will be Deepwater's next revolutionary investment?
You mentioned in the past that frequent selling and buying is very reduced.
Now that its an ETF, how will the ETF be adjusted (ie what frequency) when the LLM tells you to make a change in a position? Immediately? Or once a week? Or what?