April 30, 2024
The Secret AI Sauce for Market-Beating Returns
Dear Subscriber,
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| By Karen Riccio |
For decades, the ability for hot-shot, Wall Street traders to buy and sell stocks at lightning speeds left average investors in the dust.
However, AI is quickly leveling the playing field.
In a moment, I’ll share a new project that opens the door — for the first time — to outsized, AI-led profits for retail investors.
First, let’s take a look at the impact of technology on investing over the years … and how we evolved to where we are today.
Considered one of the trailblazers in implementing quantitative models to optimize returns, Ray Dalio’s Bridgewaters’s Associates — founded in 1975 — set the groundwork for the industry’s future.
Quantitative models use mathematics, probability and statistical analysis, as well as data analytics to identify trends, price patterns, momentum and other factors that impact stocks.
Just seven years later, mathematician and code breaker James Simons founded Renaissance Technologies and embraced a version of AI, albeit a very immature one, to manage his flagship hedge fund. Launched in 1988, Medallion Fund attracted a lot of attention as having the “best record in investing history.”
Simons claims his team of mathematicians, statisticians and data scientists paid little attention to fundamental analysis, valuation or future catalysts. Instead, they focused on price patterns and relied on vast swaths of data to perfect their art.
The model didn’t disappoint. Since 1988, the Medallion Fund has returned an average annual return of 62%.
It’s a great success story, but you and I can’t be a part of it. The fund has been closed to outside investors since 1993.
The explosion in automation, speed, data processing and access to “everything digital” in the 1990s gave rise to high-frequency trading (HFT). It handed traders using the fastest machines a distinct advantage over the rest of the investment world.
Once the SEC authorized electronic exchanges, it forever changed the way stocks were bought and sold. In fact, that regulation basically solidified HFT a place in Wall Street’s future. It also sent the average number of shares traded through the roof in 2005, reaching a peak in 2009.
By the turn of the 21st century, HFT trades had an execution time of several seconds. By 2010, it fell to milliseconds, and even microseconds. It’s even quicker today.
HFT firms did this by using sophisticated computer algorithms, often running on servers housed right next to exchanges’ own machines. High-speed market data feeds allowed them to buy and sell securities in rapid-fire fashion.
Back then, the infusion of technology centered mostly on how quickly trades could be placed.
Speed remains a cog in the investment world. However, it’s not nearly as key — unless we’re referring to speed as it relates to processing enormous amount of data. Today, intelligence is the great differentiator.
Used smartly, AI-infused investing models can be very successful. Best of all, AI isn’t a tool only for the rich and famous or high-tech firms with deep pockets. Retail investors are experimenting with AI.
But the jury is still out on how laymen, with less technical or investment knowledge than the pros, can tap into AI’s potential.
The biggest proponents, users and beneficiaries of AI-infused models for now are those who stand to win or lose the most: financial advisors, fund managers … and their clients.
One of the most well-known fund families, the Vanguard Group, added AI into its fundamentally driven quant process last year. The world’s second-largest asset manager with $7.7 trillion under management is betting that its new linguistic and data-analysis capabilities will help existing strategies adapt to changing economic and market conditions.
The $8.4 billion Vanguard Strategic Equity Fund (VSEQX) beat its benchmark and most peers in 2023, as did the $1.6 billion Vanguard Strategic Small-Cap Equity Fund (VSTCX).
The idea is that a machine is better at figuring out nonlinear relationships across a number of variables.
For instance, it might deduce that the strength of a corporate balance sheet doesn’t really matter until interest rates cross a key level … or until economic growth slows past a certain point.
The investment world has only begun tapping into AI’s potential as a legitimate tool for selecting and managing portfolio positions. You can probably expect inconsistencies as firms experiment with integrating AI into existing models.
Not from us, though. We’ve been working on AI for years and developed our own proprietary AI algorithms.
But this is the first time we’re elevating AI to a much higher level — the first time we’re putting AI in the driver’s seat.
That’s what makes it totally different from anything else we’ve done before. Plus, we’re mixing in machine learning (ML).
Elon Musk’s team uses ML to fine-tune Tesla’s self-driving technology. And ChatGPT uses it to process 10 million user tasks each day.
Here at Weiss, however, we believe the unbiased nature of our independent ratings and the mega-database we spent $25 million building truly set us apart from the pack.
Dr. Martin Weiss calls the model “the best-performing trading system in the world, and the crowning technological achievement of his 53-year career.”
“We used the same top-of-the-line AI tools as NVIDIA and Goldman Sachs to grow our portfolio by 10,945%. This is my crowning achievement — the most important technology we’ve ever created.”
— Dr. Martin Weiss
I urge you to join him for its official grand reveal next Tuesday, May 7 at 2 p.m. Eastern. You can secure your spot by clicking here.
Until next time,
Karen Riccio
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