[Editor’s Note: This is the second installment of our three-part series on how artificial intelligence can give you an investing “edge.”
In Part I, I explained how I started using AI principles and the power of data and analysis.
In Part II here today, we’ll peek under the hood and I’ll give you a glimpse of how it all comes together. And
In Part III, which I’ll send you Saturday, we’ll bring it all together and look at some of the results.]
Back on Feb. 2, the shares of social-media heavyweight Meta Platforms (META) zoomed 23% in a single day’s trading.
But five days before that, my Quantum Edge trading system signaled that a rally was in the offing.
I want to show you the signal, the system, and how it gets extra muscle from artificial intelligence.
The signal that I’m talking about was triggered by Big Money buying, which I’ve marked on this META chart below.
The yellow arrow shows the first signal, and the blue arrow shows the surge five days later – which also generated a signal. Just as importantly, notice the light blue shaded area, which is the stock’s price.
Here’s one other point that I want to drive home here… META shares have zoomed another 40% since that second signal.
The chart is terrific for visualization. But what it doesn’t show are the massive amounts of data, computing power, and sophisticated algorithms that get us to this point.
This is possible thanks to artificial intelligence – which, as you know, is taking the world by storm right now. At its core, AI leverages advanced computing power to analyze mind-bending amounts of data.
The world’s fastest computer, known as “Frontier,” lives at the Oak Ridge National Laboratory in Tennessee. And it can perform one quintillion calculations each and every second. (That’s 1,000,000,000,000,000,000, for you number folks out there.)
I don’t have that kind of computing power. But I don’t need it. My Quantum Edge computers already process more than one million data points on more than 6,000 stocks every single morning… And this is a tremendous edge in finding stocks best positioned to move higher.
That kind of analytical firepower wasn’t available even just a couple of decades ago.
And it reveals that there are fewer of those big-money opportunities than you’d ever think.
I’ve mentioned – many times – the epiphany-level research done by Hendrik Bessembinder, an economist and professor at Arizona State University.
For the last 100 years, just 4% of stocks delivered 100% of the stock market’s net gain above U.S. Treasury bonds.
Or to put it another way: 96% of all stocks over the last century failed to beat Treasuries.
To find those needles in the global stock-market haystack requires screening those millions of data points daily.
In fact, it demands that we analyze the right factors, at the right time and in the right way.
AI makes that doable.
Thanks to artificial intelligence, we can already analyze, sort, and rank more data points, combinations, scenarios, and patterns than any human could in his or her lifetime.
And we can do that in seconds.
So, let’s open the hood of this powerful Quantum Edge engine and see what’s underneath.
The Data May Not Be Exciting, But the Results Are
As we established, the META chart helps us “see” the final product and is great for visualization. But the nuts-and-bolts programming and data aren’t nearly as interesting to look at.
In fact, the code I wrote to identify this unusual buying is a bunch of 1s and 0s.
And the “output” – the daily screens that display the results of algorithmic analysis – are an admittedly pedestrian-looking Microsoft Excel file.
Below is a screenshot of exactly that. You can see META with a green “buy” signal indicating unusual activity for Jan. 27, 2023:
Not very exciting to look at, is it?
But if it allows us to make money, I’d say that’s pretty exciting.
The AI Version of Wall Street’s Elite
Now, not every stock with Big Money buy signals is a winner. As cool as those are, investing in moneymakers is not that simple.
In fact, some stocks with buy signals aren’t even great businesses. Surprise, surprise… Even Big Money buys junk sometimes.
But we don’t want the junk. That’s why our daily analysis also tells us if a stock being scooped up by Big Money is a quality business that trades well.
This is where AI help us again. As I mentioned last time, in writing the algorithms, I basically “uploaded” the minds and methods of the brightest investors out there: the fundamental and technical factors that are most important – because they best predict higher prices.
Of the roughly 6,000 stocks our Quantum Edge system analyzes every day, each has about 120 data points… which are boiled down to 29 of the most predictive factors… which are further boiled down to three scores.
Below is another “output” for Jan. 27 showing raw data. The important thing to notice here is the three numbers to the far right (in the highlighted yellow line)… 70.69, 0.6765, and 0.75:
Those are the…
- Quantum Score of 70.7.
- Technical Score of 67.7.
- And Fundamental Score of 75.0.
The Quantum Score is the ultimate single number that measures the quality of a stock. Historical data going back to 1990 has shown me that stocks with a Quantum Score of 70 or higher are indeed high quality – and have a much higher likelihood of rising in price than those with lower scores.
To give you a sense of scale, here’s what the “output” for the entire stock universe for one single day looks like, when I shrink it down to a normal-sized screen shot. Actually, the file can’t even fit on one page, so you are looking at only 60,600 fields of the 1,363,725 data points for that one day’s file.
That yellow arrow up in the right corner points to the data for META:
You are essentially peering into the AI version of Wall Street’s elite investors, coded by yours truly.
Our proven system does convert this data into those easier-to-digest charts and visualizations. But, to be honest, I like working in Excel, where I can manipulate and sort the data as I add my own analysis in the end.
There are a few more steps to zooming in on those rare stocks best-positioned to make money, and we’ll talk about this next time.
Editor, Jason Bodner’s Power Trends