While Everyone Else Figures Out AI, We’re Using It to Make Money

Artificial intelligence is fascinating, amazing, and scary.

The technology is exceedingly 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, AI can help design new drugs faster than ever.

But then there’s the other camp of folks 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.

Just last night, the man called the Godfather of AI, British computer scientist Geoffrey Hinton, told 60 Minutes that we do indeed need to worry about machines getting smarter. “One of the ways these systems might escape control is by writing their own computer code to modify themselves,” he said. “And that’s something we need to seriously worry about.”

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.

In how AI can help us make money…

I Was Using AI Before It was “a Thing”

My own meandering journey into the land of AI and picking great stocks took hold during the 14 years I worked on Wall Street. In the nine years since, I’ve worked to see what factors most-reliably tell me that a stock will surge in price.

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 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 in fact the best – to find out exactly 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 did they look for with a company’s earnings? How about its sales? What volume should I look at? Any particular trends in volatility? What about debt levels? How much cash should a company have? How important is momentum? And on and on…

I was engaging in a form of AI development, though I didn’t think of it in those terms at the time.

But that’s exactly what it was: I took the answers to my questions, absorbed all that wisdom, back tested it to find out what worked and what didn’t, and coded that combined “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 and made it “smarter.”

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.

And that’s part of it. But there’s a lot more going on, and it’s not always visible on a chart with just 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.

Or could they?

I have long believed that the “smart money” sniffs such things out before everyday investors. That was true here.

Look now at this chart from my Quantum Edge system

Source: MAPsignals.com

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 the “what” matters more. 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 algorithms for my system to be able to retrieve and analyze more than a million data points on more than 6,000 stocks every single trading day. And with that data getting added to more than 32 years of historical 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 three decades of data.

That’s how I know AI can help us make money.

Talk soon,

Jason Bodner’s Power Trends

P.S. AI is also a massive opportunity in and of itself as companies all over the world rush to incorporate it.

In fact, I was asked recently where I would invest a million dollars right now, and my answer was an AI company.

It’s a small tech stock that meets all of our quantum criteria… and it’s my favorite play on the AI boom that has already created $5 trillion in new wealth.

I put all of the details in a new report called M.A.P.’s #1 Move for the $5 Trillion A.I. Reckoning.

Click here to learn how you can access it today – along with all of my recent recommendations – and put the AI advantage to work for you.