{"id":26861,"date":"2026-04-15T07:30:00","date_gmt":"2026-04-15T11:30:00","guid":{"rendered":"https:\/\/jeffclarktrader.com\/market-minute\/?p=26861"},"modified":"2026-04-14T14:18:27","modified_gmt":"2026-04-14T18:18:27","slug":"this-ai-flags-the-days-best-trades-12-hours-in-advance","status":"publish","type":"post","link":"https:\/\/jeffclarktrader.com\/market-minute\/this-ai-flags-the-days-best-trades-12-hours-in-advance\/","title":{"rendered":"This AI Flags the Day’s Best Trades 12 Hours in Advance"},"content":{"rendered":"
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Managing Editor’s Note: <\/strong>Yesterday, Tradesmith CEO Keith Kaplan teased a game-changing approach to wealth building in Market Minute<\/a>. <\/em>Today, he’s unveiling Tradesmith’s newest and most powerful tool.<\/p>\n

You can test drive it for free right here<\/a> for a full week, and make sure you read on for how this powerful system works in the most volatile market conditions…<\/p>\n<\/div>\n

This AI Flags the Day’s Best Trades 12 Hours in Advance<\/h2>\n

BY KEITH KAPLAN, CEO, TRADESMITH<\/strong><\/p>\n

“There is an entity that cannot be defeated.”<\/em><\/p>\n

That’s how Lee Sedol – the world’s greatest Go player – described AI after losing a five-game contest against Google’s AlphaGo AI model in Seoul in March 2016.<\/p>\n

Go was invented in China more than 2,500 years ago. Two players place black and white stones on a grid, trying to capture each other’s pieces.<\/p>\n

Stones on a Go board (Source: Wikimedia Commons)<\/em><\/p>\n

It looks easy. But it contains more possible positions than there are atoms in the observable universe. The best players win by feel and intuition rather than brute calculation.<\/p>\n

So, Sedol thought he was safe. The game was too creative – too deeply human – for a machine to crack. Before the match, he predicted he’d win every game.<\/p>\n

Then came Move 37 in the second game.<\/p>\n

AlphaGo placed a stone in a position no normal player would make – a move so strange that one commentator blurted out, “That’s not a human move.”<\/p>\n

He was right.<\/p>\n

AlphaGo’s analysis showed that a human player would make that move less than 1 in 10,000 times. But it turned the tide in AlphaGo’s favor, and Sedol lost the game.<\/p>\n

He went on to lose the contest 4-1.<\/p>\n

The machine wasn’t smarter. But it could see patterns no human eye could. And that was enough to defeat the world’s best player.<\/p>\n

It’s a cautionary tale for investors today. AI models are way better at recognizing patterns now than they were a decade ago. And there’s no domain richer in hidden patterns – or more ruthlessly efficient at rewarding those who spot them and punishing those who miss them – than the stock market.<\/p>\n

That’s why my team and I at TradeSmith have spent the last 12 months building a new application of AI for self-directed investors like you.<\/p>\n

It uses the same principles that defeated the world’s greatest Go player to spot patterns that flag the day’s most promising trades – 90 minutes before <\/em>they happen.<\/p>\n

We just opened up a beta version so you can test drive it ahead of the April 22 launch event. I’ll show you how it works today – and pass on the link where you can try it out for free.<\/p>\n

We’ve Gone Deeper Than Ever Before<\/h2>\n

TradeSmith is one of the world’s largest financial technology firms for self-directed investors.<\/p>\n

We’ve invested more than $32 million to create hedge fund-level analytical systems and strategies for folks like you. But we’ve never gone this deep.<\/p>\n

Our new AI-powered trading system doesn’t look at balance sheets… read earnings reports… or follow news headlines. Instead, it detects tiny anomalies in stocks’ historical data. Then it finds statistical connections between them that a human analyst would never find.<\/p>\n

Think of it like a “thumbprint.” Every great trade has one. A unique alignment of factors – technical indicators, price patterns, market conditions – that has lined up before.<\/p>\n

When those factors align again, our system flags a high-probability setup. Some with historical accuracy rates of 90% or more.<\/p>\n

Here’s what happens when we tested it out.<\/p>\n

Turning Patterns Into Profits<\/h2>\n

In January, our system flagged a trade in Qnity Electronics (Q)<\/strong> – a company I’d never heard of before.<\/p>\n

It identified three factors that had aligned only four times over the past decade. Every time those same factors lined up for Q, the stock went up.<\/p>\n

On January 28, this signal fired again – and over the next 30 days Q shares jumped 26%.<\/p>\n\n

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Or take AI chipmaker Advanced Micro Devices (AMD)<\/strong>. On a recent signal, our system forecast an 8.4% move in 14 days, based on a pattern with 95% historical accuracy.<\/p>\n

The result was an 8.1% gain in 48 hours.<\/p>\n\n

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Or take another popular AI stock, Palantir (PLTR)<\/strong>. Our system signaled a 5.8% move in nine days, again with a historical accuracy rate of 95%. The result was a 15.1% gain in seven days – nearly three times the forecasted return.<\/p>\n\n

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These returns are from trading our signals with stocks. Here’s what those same signals produced using options:<\/p>\n