Is the N.E.W. System an AI-Driven 'Renaissance' Moment for Main Street Investors?

Artificial intelligence is driving the next evolution of "quant" investing...

Quantitative investing is any type of system based purely on numbers, rather than human judgement.

And perhaps the most famous quant firm of all time is Renaissance Technologies.

This secretive hedge fund, founded by the late mathematician Jim Simons, is often considered the most successful money manager in history.

And what they achieved for Wall Street insiders was a foreshadowing of what Whitney Tilson's New Engine of Wealth ("N.E.W.") System is aiming to do for regular Main Street investors...

'The Man Who Solved the Market'

The secret to Renaissance's success was not traditional stock picking. It was data and algorithms...

Renaissance was the pioneer of quantitative trading, employing PhDs in math, physics, and computer science. In Simons' obituary last year, the New York Times noted...

After publishing breakthrough studies in mathematics that would play a seminal role in quantum field theory, string theory and condensed matter physics, Mr. Simons decided to apply his genius to a more prosaic subject — making as much money as he could in as short a time as possible.

So at age 40 he opened a storefront office in a Long Island strip mall and set about proving that trading commodities, currencies, stocks and bonds could be nearly as predictable as calculus and partial differential equations. Spurning financial analysts and business school graduates, he hired like-minded mathematicians and scientists.

Renaissance's flagship Medallion Fund, run since the late 1980s, earned more than $100 billion in trading profits... and averaged jaw-dropping 66% annual returns before fees.

To put those returns into perspective, $1,000 invested in the Medallion Fund in 1988 would have grown to more than $46 billion by 2024.

But for years, Renaissance Technologies was completely off-limits to ordinary investors. The Medallion Fund stopped accepting outside capital in 1993 once they realized how powerful their "money-printing machine" was.

The only way to get a piece was to work there. And that was an exclusive group indeed.

Gregory Zuckerman put it like this in the introduction of his book, The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution, when talking about the 300 or so employees at the firm:

The average Renaissance employee has nearly $50 million just in the firm's own hedge funds. Simons and his team truly create wealth in the manner of fairy tales full of kings, straw, and lots and lots of gold.

To do that, they gathered massive datasets – everything from stock prices to obscure market metrics – and let computers find patterns and signals that humans might overlook.

In essence, they turned investing into a big pattern-recognition problem, much like AI does.

Bringing AI-Driven Investing to Main Street Investors

Until very recently, building something like Renaissance required immense resources... from supercomputers to pricey data feeds and top-tier mathematicians and scientists.

Renaissance doesn't share much, but it does say that its research database grows by "more than 40 terabytes a day" and it uses 52,000 computer cores for its algorithms. It's the "commercial version of the Manhattan Project," according to Andrew Lo, a Massachusetts Institute of Technology finance professor and chairman of a quant research firm.

And last year, in Stansberry Research's first quantitative model portfolio, our Director of Research Matt Weinschenk wrote:

Renaissance Technologies [...] employs more than 150 researchers who comb through a "petabyte scale" data warehouse. (Your desktop computer may have a couple hundred gigabytes of data. Each petabyte is 1 million gigabytes.)

For individual investors, using a quantitative strategy is just too much work. Plus, the technology and amount of data needed make such a system prohibitively expensive.

Fortunately, with Stansberry Research's world of resources, we can bring quant investing to you...

Matt noted that even once you have an understanding of the math and theory behind building a quant portfolio, you then need a complete database of stocks and their financials.

That's not cheap. It costs hundreds of thousands of dollars per year in data feeds, plus salaries for researchers and experts... and even more money to pay for the computing power to run through all the permutations.

So while many hedge funds have developed this type of quantitative portfolio, there's little chance that they'd share these portfolios with everyday Main Street investors.

But today, thanks to the revolution in AI, that's changing...

Computing power has gotten cheaper. Data is more accessible than ever.

And democratizing access to AI-driven quant investing is exactly the goal of Whitney Tilson's N.E.W. System.

The N.E.W. System Helps Make AI Work For You

Think of the N.E.W. System as a Renaissance-style approach to the market.

It's not the same, of course. Stansberry Research doesn't manage money. Despite a long-term track record that could go toe-to-toe with some of the best-known funds on Wall Street, it has never taken a cent from its members in performance fees. (Learn more about Stansberry Research here.)

Instead, Stansberry's business model is strictly focused on publishing research and investment recommendations. That means its analysts, like N.E.W. System editor Whitney Tilson, only succeed when their ideas make their subscribers money.

And the publishing firm isn't secretive... After all, they're literally sharing the entire N.E.W. System model portfolio with their subscribers for $149 a year.

But the philosophy behind their approach is similar... to use the raw power of vast amounts of data and an algorithmic strategy to both improve returns and reduce risk.

In short: The N.E.W. System is a way to make AI work for you.

Each quarter, the N.E.W. System scans thousands of investable stocks and runs them through the proprietary Stansberry Score.

It's looking for the top 20 stocks in the market... stocks that meet Stansberry's strict capital-efficiency, financial, and valuation criteria.

The system's next step is to take the stocks with high Stansberry Scores and apply an AI algorithm to not only select the best-of-the-best stocks, but also to create a diversified portfolio. Whitney explains it like this...

As an investor, you've heard about the benefits of diversification.

And while finding "good stocks" is a big part of investing, professionals actually spend much more time thinking about how to combine those stocks into a proper portfolio.

Most individuals don't think enough about such "portfolio construction." That's because it's hard. You have to think about dozens of stocks at the same time. And it involves a lot of graduate-level math and statistics.

That kind of thinking, though, is easy for AI.

The overarching goal is to build a model portfolio that balances risks and considers the correlations of each stock to earn better, safer returns.

And again, unlike Renaissance Technologies... it's available to everyone.

As Whitney puts it, the N.E.W. System is like having "the same kind of powerful advantage Wall Street firms use to make billions of dollars every year in all market conditions... But with a big twist that has never been possible for regular people until today."