One AI-powered test produced results that surprised Lewis.
Listen to the audio version of this article (generated by artificial intelligence).
Legendary investor Louis Navellier spent nearly five decades building quantitative systems to identify winning stocks. So, when he says that AI might be the biggest advance he’s seen in his career, we take notice.
On Sunday digestLewis explores how AI is already transforming complex fields like medicine and scientific research – and why he believes the same technology is poised to reshape investing.
Along the way, he revisits the “eureka moment” that launched his investing career, explains how his data-driven approach has identified hundreds of major stock winners over the years, and shares why a new collaboration with TradeSmith has him more excited about the future of investing than anything he’s seen in decades.
Lewis delved into this collaboration during his presentation last week with TradeSmith CEO Keith Kaplan. They showed how AI can help investors become more tactical in volatile markets. You can watch the free replay here.
Bottom line: If Lewis is right, AI will not only change the companies we invest in, it will fundamentally change the way we invest.
I’ll let him take it from here
I wish you a good evening,
Jeff Remsburg
If you are under 50 and stay healthy, it is possible to live to be 150.
To you and me, this may sound like science fiction. But for Demis Hassabis, it seems conservative.
Hassabis is the computer programmer and neuroscientist who founded DeepMind – the leading deep learning lab that Google acquired in 2014.
Deep learning is a method of training programs to recognize patterns by feeding them massive amounts of data and allowing them to learn from their mistakes. It’s the core technology behind OpenAI’s ChatGPT, Anthropic’s Claude, Google’s Gemini, and most of what people mean when they say “AI” today.
In 2024, Hassabis won the Nobel Prize in Chemistry for building an artificial intelligence model — called AlphaFold2 — that mapped all 200 million known proteins. This led to a revolution in drug discovery.
Most medications work by binding to a specific protein in your body — just like putting a key in a lock. For 50 years, discovering what these locks look like has been extremely slow and expensive, stifling the entire drug discovery process.
Thanks to AlphaFold2 mapping, what used to take researchers years in the lab now takes hours on the computer.
Progress is so rapid that Hassabis estimates that we will cure all diseases within 10 years.
I’m 67 – I’m over the 50 mark he’s talking about. But when I look at the results of medical research in just the past two months, he may be right:
- A drug has succeeded in doubling the survival rate in pancreatic cancer, which is the most dangerous type of cancer of all.
- A one-time gene-editing injection permanently lowers bad cholesterol by 62% from a single dose.
- A lung cancer pill suppressed a metastatic tumor for a full five years, longer than any drug has ever controlled it.
- Mayo Clinic has built an artificial intelligence system that detects pancreatic cancer from routine CT scans up to three years before a doctor can detect it.
- Eli Lilly’s new anti-obesity drug achieved a 30% body weight loss in its phase 3 trial — and along the way, reduced knee osteoarthritis pain by 76%.
These are not random hacks. They were all discovered, accelerated, or made possible by Hassabis’ deep learning AI models.
And guys, these models are only accelerating as the AI learns to write code to create more powerful models… which writes code to create more powerful models… and so on.
Which brings me to a question I’ve been thinking about a lot lately.
If AI rewrites what is possible in a field as complex as human biology, what will it do to financial markets?
I’ve spent 47 years building computer systems to find them Growth stocks Before the crowd catches up. So, I know what it’s like when new technology changes the rules of the game for investors.
In the 1970s, I was one of the few people using a computer to pick stocks. Most of my colleagues thought it was eccentric at best… and a fool’s errand at worst. Today, computers are responsible for about 80% of daily stock trading volume.
I believe that what is coming with artificial intelligence is a change of much greater magnitude.
I’ll show you what I mean in a minute – including how adding AI to my quantitative models could lead to a 615% gain on a stock like DXB Enterprises Inc. (DXBE) To a winner of 3,626%, or a win of 292% Broadcom (AVG) To 6,284%.
But first let me take you back to the early 1970s when I had my first “eureka moment” about how machines could unlock the secrets of the stock market.
My eureka moment
It was my freshman year at Cal State Hayward (now Cal State East Bay), where I was studying Finance.
One of my professors worked for Wells Fargo, where he used its mainframe to build stock market indexes that were just emerging. He asked me if I could help.
The flashiest technology I’d touched upon up to that point was the slide rule. Access to this mainframe would have been a 19th century gold prospector’s pitch for a diesel-powered excavator.
My job was to build a model portfolio that mimicked the S&P 500 using only 320 stocks. But something unexpected happened. Instead of just tracking the market, my version beats it.
This wasn’t supposed to happen. The prevailing theory of the time – and repeated as gospel by every financial book – was that you couldn’t beat the market consistently. It was impossible.
My data said otherwise
So, I dug deeper. Statistical tests have been performed. I found a pattern that would define the next five decades of my career. Some stocks move independently of the broader market and have their own signals. Find it early enough, and the gains can be extraordinary.
People on Wall Street call it “alpha.” From that moment on, I became obsessed with building systems to find it.
Nearly 700 gains 100% or more
This discovery launched a career I never could have expected.
Over the next five decades, I built quantitative models that powered some of America’s most successful investment newsletters.
My system has identified 676 stocks that have more than doubled – including recommendations like… Microsoft Corporation (MSFT) In 1987, Nike company (to) and Apple Inc. (Apple) In 1988, W Nvidia company (NVDA) It was a full 17 years before most people heard about ChatGPT.
The latter alone would have turned $1,000 into over $1 million.
None of these victories came from intuition or gut feelings. It came from what I discovered with the help of the Wells Fargo mainframe in the 1970s — a systematic, data-driven process of finding fundamentally outperforming stocks backed by strong institutional buying pressure.
The process has become more precise over the decades. The data has become richer. Models have become more powerful.
In other words, I’ve spent my career searching for… CrA tenth of cry From the stock market. But I’ve never had access to a technique as powerful as what I’m about to show you.
The difference is extraordinary
As I like to say, good stocks bounce like fresh tennis balls, while bad stocks fall like rocks. The key is to know the difference before the market starts to shake.
For this reason, over the past year I have been working with the team at Want Smith For something I’ve never tried before.
If you don’t know them already, they are the fintech company behind some of the most advanced portfolio tools available to retail investors today.
Together, we’ve built a new form of AI that takes me Stock grader The system adds a layer that didn’t exist before: an accurate, data-driven signal for knowing when to enter and when to exit the stocks I’m recommending.
It includes a layer of the same kind of pattern-recognition AI technology that diagnoses cancer three years earlier and designs drugs in hours instead of years.
The difference it makes is extraordinary.
takes Appfolio Company (APPF)a stock I recommended in 2017.
Anyone who acted on this recommendation enjoyed an annual gain of 20%. It doubles over time, which is excellent. But according to our previous tests, this new AI-powered system could have achieved annual gains of 74%.
Or take NEXSTAR MEDIA GROUP (NXST)Which I recommended in 2013. The average annual profit of 23% becomes 173%.
The same inventory over the same time period. Just smarter timing.
Across the board, backtesting indicates that pairing this new AI with my Stock Grader assessments can generate up to 20x more money than following Stock Grader alone.
That’s why I say this is the biggest advantage I’ve seen in my 47 years as a professional investor. It’s not a new stock picking system, it’s a new layer of intelligence on top of what you’ve already built.
And if we get more volatility in the stock market this summer, I think this kind of intelligence could be more valuable than ever.
Biggest ledge I’ve seen
In the 1970s, the idea of using a computer to pick stocks seemed absurd to most people on Wall Street. I did it anyway. The results spoke for themselves.
Today, the idea that AI can reliably improve on a 47-year track record may seem hard to believe, too. I understood this doubt. I felt it myself. But then I looked at the test and had to admit that the AI as well as my system worked like gangbusters.
I have been looking for edges in this market for 47 years. I’ve never seen one like this.
To find out exactly how it works — and get the full list of stocks it flags as hot buys and sells — Click here to watch a replay of my event with TradeSmith CEO, Keith Kaplan.
During the presentation, you’ll be able to see TradeSmith’s Short-term health index.
While the main focus of Stock Grader is on What Stocks to buy, short term health is everything when To buy it.
It allows you to write any bar to see if a stock is a short-term buy or sell based on a simple traffic light system. Green means buy. Yellow means contract. Red means sale.
Here’s the link to learn all about the Short-Term Health Index – and how Stock Grader improves it.
sincerely,
Louis Navellier
Senior investment analyst, Investor location
