Trading Tips Blog

Dan Ives, Wedbush Securities' resident tech bull, just dropped a thesis that might actually make sense in the AI chaos: forget the flashy language models everyone's obsessing over. The real winners? Companies that help enterprises actually *use* their data. Here's the thing—everyone's been chasing ChatGPT knockoffs and LLM hype, but Ives reckons that's about to get commoditized faster than you can say "open-source model." The actual money is in the data layer: the infrastructure that turns a company's messy, internal data ...
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Look, everyone's obsessed with the next big tech unicorn, but here's the thing—sometimes the best investments are the boring ones that actually make money. Value investing isn't sexy, but it works. Warren Buffett didn't get rich chasing meme stocks; he found companies trading for less than they're worth and waited for the market to catch up. So what makes a stock "valuable"? Think of it like finding a designer handbag at a thrift store. The bag is still quality, still functional, ...
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Look, everyone's been obsessed with the flashy AI stuff—ChatGPT, Claude, all those large language models that can write your emails for you. But here's the thing: Dan Ives, one of Wall Street's biggest tech bulls, just dropped some knowledge that most people are sleeping on. The real money in AI isn't in the models themselves. It's in the data layer. Think of it like this: LLMs are becoming the commodity. They're getting cheaper, more accessible, and honestly, less differentiated by the ...
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Look, everyone's freaking out about whether we're in an AI bubble. Ray Dalio's sounding the alarm. Fast Company's drawing parallels to 1999. Meanwhile, Goldman Sachs CEO David Solomon's saying we might be earlier in the cycle than later. So which is it? Here's the thing: they're both kind of right, but they're also both missing the forest for the trees. The Bear Case Isn't Crazy Let's be fair to the pessimists. When only 20 out of 500 S&P 500 companies hit all-time highs while ...
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Remember when everyone was convinced Big Tech's AI spending would eventually hit a wall? Yeah, about that. Goldman Sachs just threw a wrench into that narrative, and it's a pretty hefty one. The bank's latest analysis suggests that Wall Street has been massively underestimating how much hyperscalers—think Google, Amazon, Microsoft—will actually spend on AI infrastructure. We're talking roughly $1.1 trillion in 2027, compared to the $920 billion Wall Street is currently expecting. In a bullish scenario? Try $1.4 trillion. That's not ...
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The bull market's been charging for three years straight now, and everyone's wondering: does it keep going, or does it finally run out of steam? Here's the thing—2025 was wild. The S&P 500 climbed about 18% year-to-date, the Nasdaq jumped 22%, and the Dow hit all-time highs. That's on top of 24% and 23% gains in 2023 and 2024, respectively. If you're keeping score, that's three consecutive years of double-digit returns. Not bad. But here's where it gets interesting: Wall Street can't ...
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Remember when everyone was convinced AI would destroy the world? Now they're convinced it'll destroy their portfolios. Plot twist: they're probably wrong on both counts. Last week, the market threw a tantrum over an AI selloff. Broadcom got blamed for kicking it off, but here's the thing—the company just posted nearly 50% revenue growth, 80% semiconductor revenue growth, and a $30 billion backlog. That's not weakness; that's a company drowning in demand. If that's a red flag, I'm a flamingo. So what ...
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Goldman Sachs reveals Wall Street is underestimating AI infrastructure spending—potentially $1.1 trillion in 2027. Token consumption expected to explode 24x by 2030, but productivity gains remain unproven ...
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