The AI Predicting Storms Is Now Giving Investors an Edge

Editor's note: Forecasting the market has long been like forecasting the weather – unpredictable, volatile, and ruled by chaos. According to Keith Kaplan, CEO of our corporate affiliate TradeSmith, both weather and market storms can appear in seconds because of tiny, interconnected shocks. In this issue – adapted from the free TradeSmith Daily e-letter – Keith reveals how advanced AI is starting to make sense of this turbulence... giving investors a new edge.

In early July 2024, Hurricane Beryl was tearing across the Caribbean with winds topping 165 mph. It killed 36 people, left millions without power, and caused billions of dollars in damage.

For decades, forecasters have used giant supercomputers to track storms like this. But because of complex physics equations, it can take more than an hour to produce a single 10-day forecast.

When Beryl formed, forecasts from a top European weather agency pointed to Mexico as the likely target for landfall.

But an experimental forecasting system called GraphCast disagreed. Days in advance, it predicted the storm would make landfall in Texas.

When Beryl struck Matagorda Bay, Texas on July 8, it was GraphCast – which can run on something as small as a laptop – that had been right all along.

GraphCast was created by Google's DeepMind AI lab. It's trained on 40 years of weather data. And it can produce a 10-day forecast in 60 seconds.

Instead of solving complex equations, it spots hidden patterns in past weather data. This allows it to see further and faster than traditional physics-based models.

This was a turning point for meteorology. A laptop-scale AI model beat the most powerful forecasting engines on Earth.

And if AI can decode the weather, what can it do with the other great chaotic system of modern life: the stock market?

My team of 74 researchers and developers at TradeSmith put our $8 million annual budget to work to find out.

Today, I'll show you how it works – and how you can use it to dramatically increase your odds of success as an investor. But first, it's important to understand the common thread between predicting storm paths and stock market prices...

A Butterfly Flaps Its Wings...

In 1961, Massachusetts Institute of Technology meteorologist Edward Lorenz was tinkering with a rudimentary weather model on a Royal McBee computer.

It was the size of a fridge, spat out forecasts on long rolls of paper, and could take an hour just to process a handful of equations.

To save time, Lorenz tried a shortcut. He rounded one of his inputs from six decimal points to three. And that change transformed a calm weather pattern into a raging storm.

Lorenz discovered that tiny changes can snowball into huge effects. He called it the "butterfly effect."

Weather systems can shift on a dime because they're dynamic, not linear. Even the tiniest change, like a gust of wind or a seemingly minor increase in humidity, can cascade into a wildly different outcome.

Markets are the same.

Every trading day, markets absorb thousands of tiny shocks. A comment from the Federal Reserve, a company's surprise earnings miss, or a social media post can shift sentiment.

That's why the world's best hedge funds have spent decades building algorithms to capture them. Take Jim Simons' Medallion Fund. It has averaged 66% annual returns since 1988 by spotting financial butterfly effects hidden in vast stock market datasets.

At their core, forecasting storms and forecasting stock prices face the same problem. Both are dynamic systems where tiny changes create outsized consequences.

Funds like Medallion keep their edge locked away...

But at TradeSmith, we built our own Super AI to read the market's turbulence the way GraphCast reads the weather.

It's nearly impossible to replicate because it requires decades of market data, thousands of hours of programming, and a dedicated research team to stitch it all together.

From Storm Paths to Stock Prices

Our kind of AI model is called TimeGPT.

It isn't designed to write text or generate images. Instead, it forecasts what's known as time-series data.

This is how GraphCast works. It doesn't solve physics equations from scratch. It learns from decades of weather data to see how storms grow and move.

Think of stock prices like storm tracks: data points lined up in time, where each moment connects to the ones before, and hidden patterns influence what comes next.

Our AI is built to see those storms before they hit...

For example, our back tests showed that, this past May, the model predicted Tesla (TSLA) would hit $302.89 in 21 trading days.

It reached that price faster than expected. We booked a 5.2% gain in just 24 hours. And you could have boosted it to 310% over that same 21-day period.

While that gain is impressive, we found you could have done even better with a five-stock portfolio. You simply buy the best five trades every week – with an 85% historical accuracy – and sell when they hit their projection.

Last year alone, you could have made a 602% gain with this five-stock strategy.

That's more than 30 times the return you'd have gotten holding the S&P 500 Index. And it's more than triple the return of Wall Street darling Nvidia (NVDA) in 2024.

And it's all thanks to our new "Super AI."

Just as weather forecasters don't want to miss the next hurricane, investors can't afford to miss the next "Hurricane Nvidia," "Hurricane Apple," or "Hurricane Tesla."

And with this system, investors can unlock the same edge Wall Street has kept hidden away.

Sincerely,

Keith Kaplan

Editor's note: TradeSmith's new Super AI could have the biggest impact on your wealth since the dot-com era. It spots the fewer than 1% of stocks on the verge of a massive potential jump each morning. This year alone, it could've doubled your money eight times. Soon, everyone will be using this type of financial AI to find stocks. For now, early access to Keith's presentation is still available – but it won't stay open for long.