Liz here, with a little different story for you today.

In between listening to my family fight over Minecraft, I’ve been researching exactly how much big banks and investment firms are spending on big data every year. (Anything to keep from hearing my son and my husband argue with each other about who let the square pigs out.)

Spoiler alert: it’s an obscene amount.

And there’s money in it for you.

So I’ve got a call trade for you, naturally…

And I’ve also got a look behind the scenes at Tom’s mysterious basement machine…which is basically big data on steroids.

In fact, if it catches on, it could put all these massive analytics companies out of business.

Let me show you what I mean…

This Is The Insane Amount of Big Data Spending You’ll See This Year (And How to Get Some)

I’m just going to directly quote Business Wire, because they seem trustworthy (the famous last words of Pinocchio before he was turned into a donkey).

They wrote this in 2021, but I’ve got a handy Statista chart for you that goes up all the way to 2022.

The bolding is mine. Look at this MF of a big number.

Worldwide spending on big data and business analytics (BDA) solutions is forecast to reach $215.7 billion this year, an increase of 10.1% over 2020, according to a new update to the Worldwide Big Data and Analytics Spending Guide from International Data Corporation (IDC). The forecast also shows that BDA spending will gain strength over the next five years as the global economy recovers from the COVID-19 pandemic. The compound annual growth rate (CAGR) for global BDA spending over the 2021-2025 forecast period will be 12.8%.

“Over half of all BDA spending in 2021 will go toward services with IT services accounting for more than $85 billion of the total and business services making up the remainder. The second largest segment of BDA spending this year will be software, which will see investments totaling $82 billion. Almost half of this total will go to three types of applications – End-User Query, Reporting, and Analysis Tools, Relational Data Warehouses, and Nonrelational Analytic Data Stores – with the remainder spread across the 13 remaining software categories. Software will also be the fastest growing segment of BDA spending with a five-year CAGR of 15.1%.

“Unlike many other areas of the IT services market, big data and analytics services continued to grow in 2020 as organizations relied on data insights and intelligent automation solutions to survive the COVID-19 pandemic,” said Jennifer Hamel, research manager, Analytics and Intelligent Automation Services. “The next phase of digital resiliency will spur increased investment in services to address both lingering and new challenges related to enterprise intelligence initiatives.”

Spoiler alert: the projected number for 2022 ($274.3 billion!) is even bigger.

All that big data spending basically boils down to analytic technology that helps big financial institutions figure out where to put their money and how to make more of it.

Take, for instance, J.P Morgan, which in 2019 had a $11.4 billion technology budget, up 5.6% from the previous year’s $10.8 billion. (Second largest bank tech spenders were Bank of America at an even $10 billion, and Wells Fargo at $9B.

There’s an image for ya.

In J.P. Morgan’s most recent earnings call, they delved down a little bit into just what they spend all this “tech” money on – and surprise, surprise, it’s mostly on ways to collect data and use it to generate money. (Oh, yes, and their 2021 budget is now up to $12 billion, 26% more than 2020.)

Forbes says: “The 26% boost in the bank’s 2021 tech spending covers not just software development, but investments in data and analytics, artificial intelligence and physical aspects such as data centers.”

$600 million a year goes to “research and data”, a.k.a. spying on account holders, by the way:

“As a large financial institution, JPMorgan Chase highly values effective research and data about their customers, the financial markets, and the global economy. JPMorgan Chase spends $600 million a year on research in these fields, using both broader economic data and their own massive data sets on the spending and income of their account holders, who stretch across 60 countries and half of all households in the United States.”

As you can see, the “tech” piece of the research and data pie…just for banks… is pretty big (a little less than a third of total, worldwide data spending.)

Just a few more soundbites to give you an idea of how much money big financial institutions spend on this type of stuff…

  • UBS recently bought automated wealth manager Wealthfront for $1.4 billion…
  • Goldman Sachs spends $400 million each year purchasing data from third-party sources…
  • Vanguard spends $5 million on research annually…
  • Morgan Stanley spends $4 billion every year on IT…
  • And they also purchased E*Trade (and all their systems and data) in 2020 for a cool $30 billion…

The list goes on.

As far as your piece of the pie, you could always pick up some calls on Splunk Inc (NASDAQ: SPLK), a big-a** software company with lots of specialized solutions for research and data – particularly in finance. (Here’s a mind-boggling piece from their investor presentation.)

(That reminds me of “Every Good Boy Deserves Fudge,” the way I was taught to remember the lines on the treble clef when I learned piano. EGBDF!)

Their past few earnings have looked good – and the stock trajectory looks good, too.


The calls are a little on the expensive side, but not prohibitively so.

Here’s what to do:

DOLLAR SLOTS

Action to Take:

Buy to Open SPLK June 17, 2022 $150.00 Calls for $5.50 or less.

Enter as a Good til Canceled (GTC) order.

As the Cat in the Hat said, though…

“That is not all. Oh, no. That is not all.”

Tom’s Mega Trade Machine Makes All This Data Look Like Small Potatoes

It should be pretty obvious at this point that big data is big business. (Sorry, I almost wrote “pig business,” because I’m arbiting yet another dispute about square pigs.) WHO, WHO, WHO? Who let the pigs out?

Right now, the best business schools in America, like Wharton and Columbia, are training future bankers and hedge fund managers how to apply data science to investing and trading.

But Tom has them all beat.

In fact, he and his team have just spent an entire year in their trading lab, developing and refining a new scientific method. Using advanced science and hyper computing to uncover new and exciting trades with absolutely staggering potential.

(This is the mysterious basement trading machine I’ve been telling you about.)

No one else…not J.P. Morgan…not Goldman Sachs or Wells Fargo or UBS… is using data this way.

Or getting these types of results.

Of course, Tom has sunk millions of his own money into this thing.

And it delivers the biggest, fastest gains you could possibly capture… in a matter of days.

Tom’s spent the past year back testing, breaking, and perfecting his new tech to deliver Mega Trades that could double, triple, and even 10X or more your money in a matter of days. This multi-dimensional technology has the power to:

  1. Dynamically target fast-moving stocks that have entered the hot zone.
  2. Scientifically detect price accelerations on these stocks.
  3. Pick out optimized mega trades with astounding potential.

This triple-tiered method gives you the best shot to go for one windfall after another.

Now I can’t share everything with you right now, but here’s what I can say…

After using every tool at their disposal to scan the data, run different models, overlay trend lines, backtest, analyze, you name it… Tom’s team uncovered trades that can produce outsized gains, such as a peak 517% in 2 days… 857% in 4 days… 1,792% in 3 days… even 2,547% in 1 day.

Now this may all seem incredible, even impossible.

Just look at what investing only $500 into some of the best mega trades from Tom’s backtest modeling analysis could have produced… the numbers are absolutely astonishing… we’re talking staggering windfalls.

No one else is going to show you how to find mega trades like these.

And tomorrow, Tom is going to be taking you behind the scenes… into his command center… (A.K.A BASEMENT)…where science meets technology.

You can get on the list to see how this insane data machine works, right here.

I’ll see you tomorrow, and in the meantime, hang loose.

Liz

P.S. I am really limited in what I can reveal about this machine. Tom’s right-hand woman, Rachelle, Slacked me to make sure I was not spilling any trade secrets ahead of the 1 pm reveal.

I assured her that I wasn’t:

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