[Editor’s Note: Last week’s blowout earnings and guidance from Nvidia (NVDA) supercharged the AI investment storyline. The bottom line: We’re in the early stages of a massive transformation that is equal parts exciting and scary.
I was ahead of the curve – and so are you. I’ve incorporated forms of artificial intelligence in my Quantum Edge system for over a decade. So, while others figure out the goods and bads of AI, we’ve already proven it can help us make money.
In a special two-part series beginning today, I’ll take you deep inside my system to show you how it can help us build wealth.]
AI is an emotional topic. And it’s easy to see why.
The technology is complex. It’s tough to use our “genuine intelligence” to understand… and the potential ramifications are more than a little scary.
AI proponents see the benefits of pushing our society ever deeper into technological bliss. For them, AI can only help make our lives better. For example, Wendy’s just announced it’s automating the order process – using AI-language-recognition and production software engineered by Google. So, at least the burger eaters are benefiting.
But then there’s the other camp – the naysayers – who see the dark clouds of doom building in the distance. They worry about machines taking their jobs. Or Deep Fake communication powered by AI that’s too good to be recognized as counterfeit.
High-profile people are in this camp, too: Tesla (TSLA) founder and Twitter owner Elon Musk is vocal in warning how AI might view humankind a threat to itself, and that AI might have an “ultimate goal” – whatever that may be.
Artificial Intelligence has swept in other hot terms like machine learning, neural networks, and predictive analytics – further complicating an already mind-numbing topic. In fact, there’s a whole new cottage industry of “experts” dedicated to “staying on top of the latest in AI” – an impossible task.
I’m not here to take sides in the AI debate. I have my own opinions about this transformative technology and the future, but at this point, they are just opinions. I don’t have the data yet to draw a conclusion.
But I’m an eternal optimist by nature (I find the opposite a misuse of my valuable energy and time), so I’ve focused on making AI work for me. And I do have the data in one of those areas.
I Was Using AI and Didn’t Realize It at First
My own meandering journey into the land of AI and picking great stocks took hold during the 14 years (2001- 2014) I worked on Wall Street. In the nine years that followed, I’ve worked to see what factors most-reliably tell me that a stock will surge in price. And that search brought me to quantitative analytics – and AI.
My highest position on Wall Street was North American Head of Equity Derivatives for Cantor Fitzgerald, a blue-chip investment bank. The main part of my job was matching buyers and sellers of stocks and options contracts.
But these buyers and sellers weren’t your run-of-the-mill institutional investors: They were the heavy hitters – the Big Money players who were actually the largest professional investors on the planet.
That job gave me a special window into an elite slice of Wall Street, a “club” whose members operate skillfully and stealthily – even as they heavily influence which stocks win and which ones lose.
I watched. And I learned. For years. I saw which of these investors made the most money, and I asked questions. Lots of questions.
I was determined to find out why those “best investors” were the best – to find out exactly what they thought and how they analyzed everything. These were portfolio managers, traders, risk managers, proprietary investors (who invest the firm’s money), and many more elite stock investors.
What earnings did they look for? How about sales? What volume should I look at? What trends in volatility? What debt levels? How much cash should a company have? How important is momentum? And on and on…
In all candor, I didn’t realize I was engaging in a form of AI development.
But that’s exactly what it was: I took the answers to my questions, absorbed all that wisdom, back tested it all to find out what worked and what didn’t, and coded that “intelligence” into my own algorithmic stock analysis system.
In effect, I “uploaded” the minds and methods of the brightest investors out there into a system that would identify the “right” stocks at the “right” time.
The Powerful Advantage of Data and Analysis
Along the way, I made crucial discoveries of my own. I brought my unique experience to the table. And I added to the algorithms as I uploaded more intelligence into the system.
For example, I noticed that when huge investors made moves, tell-tale signals were given off – even though they were paying professionals like me to act as secretly and stealthily as possible.
These signals were like “footprints” that could be tracked. And those footprints let me see when unusual trading was occurring. These signals weren’t visible to the naked eye, but the data retrieval and analysis models I constructed (I’m a data freak) showed me when this unusual trading activity was likely taking place.
You might think: Just look when a stock moved up or down on larger than usual volume. That thinking is on the right path, but there’s more to what’s going on, and it’s not always visible on a chart with volume.
Just take a look at this stock chart for Meta Platforms (META), the social media giant formerly known as Facebook…
You see a huge gap up in price on a day when there was also huge volume (the bars at the bottom). Investors rushed in to lift META 23% on Feb. 2, the next trading day after CEO Mark Zuckerberg declared 2023 the company’s “year of efficiency.”
And that was after the company reported a 55% drop in net income from the year before.
Nobody could have expected that, right?
But… what if you’d received a signal before Zuckerberg made his comment and bought in before the spike?
I have long believed that the “smart money” (legally) sniffs such things out before everyday investors. That was true here. Remember when I told you that unusual trading activity wasn’t always visible on everyday charts like the one above?
I highlighted that Feb. 2 price rocket and huge volume with a blue arrow, the same as on the previous chart.
But look at that yellow arrow. That points to Jan. 27, and that green bar is a signal my system picked up of unusual buying – a full 5 days before a 23% surge.
I may not know the “why” immediately, but that “what” is what matters. Institutions account for 70% to 90% of all trading volume. Being able to see where that money is flowing gives us a huge advantage.
I need massive computing power and AI algorithms for my system to be able to retrieve and analyze more than a million points of data on more than 6,000 stocks every single trading day. And that data being added to more than 32 years of data, the Quantum Edge system gets “smarter” every day.
The data shows our system picks stocks that made money roughly 70% of the time, and it outperformed the market 7-to-1 over those three decades of data.
Editor, Jason Bodner’s Power Trends
P.S. As you know, the markets are closed today for Memorial Day. Our TradeSmith offices are closed as well. We’ll be back at it again tomorrow. Enjoy the day.