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One Blogger Helped Spark NVIDIA's $600B Stock Collapse
On January 24th Brooklyn blogger Jeffrey Emanuel made the case for shorting NVIDIA, remembers MarketWatch, "due to a number of shifting tides in the AI world, including the emergence of a China-based company called DeepSeek." He published his 12,000-word post "on his personal blog and then shared it with the Value Investors Club website and across Reddit, X and other platforms." The next day he saw 35 people read his post. "But then the post started to go viral..." Well-known venture capitalist Chamath Palihapitiya shared Emanuel's post on Nvidia's short case with his 1.8 million X followers. Successful early stage investor Naval Ravikant shared the post with his 2.6 million followers... Morgan Brown, a vice president of product and growth at Dropbox, pointed to it in a thread that was viewed over 13 million times. Emanuel's own X post got nearly half a million views. He also quickly gained about 13,000 followers on the platform, going from about 2,000 to more than 15,000 followers... [Emanuel] pointed to the fact that so many people in San Jose were reading his blog post. He theorized that many of them were Nvidia employees with thousands — or even millions — of dollars worth of Nvidia stock tied up in employee stock options. With that much money in a single asset, Emanuel speculated that many were already debating whether to hold the stock or sell it to lock in profits. He believes his blog post helped convince some of them to sell. "A lot of the sell pressure you saw on Monday morning wasn't necessarily what you might think. I believe a fair amount of that was from shares that had never been active because they had been sitting in workplace.schwab.com accounts..." Emanuel stresses he's "the most bullish on AI," with MarketWatch emphasizing that "while the points Emanuel laid out in his blog post might be bearish for Nvidia, he still thinks they paint a positive future for AI." Nevertheless, Monday NVIDIA's market capitalization dropped $600 billion, which MarketWatch calls "the largest single-day market-cap drop to date for any company." What countless Wall Street firms and investment analysts had seemingly missed was being pointed out by some guy in his apartment.... Matt Levine, the prominent Bloomberg News financial columnist, noted the online chatter that claimed Emanuel's post "was an important catalyst" for the stock-market selloff and said it was a "candidate for the most impactful short research report ever." Emanuel spent the rest of the week booked solid as hedge funds paid him $1,000 per hour to speak on the phone and give his take on Nvidia and AI... Emanuel wrote that the industry may be running low on quality data to train that AI — that is, a potential "data wall" is looming that could slow down AI scaling and reduce some of that need for training resources... Some of these companies, like Alphabet, have also been investing in building out their own semiconductor chips. For a while, Nvidia's hardware has been the best for training AI, but that might not be the case forever as more companies, such as Cerebras, build better hardware. And other GPU makers like AMD are updating their drivers software to be more competitive with Nvidia... Add all these things together — unsustainable spending and data-center building, less training data to work with, better competing hardware and more efficient AI — and you get a future where it's harder to imagine Nvidia's customers spending as much as they currently are on Nvidia hardware... "If you know that a company will only earn supersized returns for a couple years, you don't apply a multiple. You certainly don't put a 30-times multiple," Emanuel told MarketWatch. The article notes that DeepSeek "is open-source and has been publishing technical papers out in the open for the past few months... The $5.6 million training-cost statistic that many investors cited for sparking the DeepSeek market panic was actually revealed in the V3 technical paper published on Dec. 26." Read more of this story at Slashdot.
On January 24th Brooklyn blogger Jeffrey Emanuel made the case for shorting NVIDIA, remembers MarketWatch, "due to a number of shifting tides in the AI world, including the emergence of a China-based company called DeepSeek."
He published his 12,000-word post "on his personal blog and then shared it with the Value Investors Club website and across Reddit, X and other platforms." The next day he saw 35 people read his post. "But then the post started to go viral..."
Well-known venture capitalist Chamath Palihapitiya shared Emanuel's post on Nvidia's short case with his 1.8 million X followers. Successful early stage investor Naval Ravikant shared the post with his 2.6 million followers... Morgan Brown, a vice president of product and growth at Dropbox, pointed to it in a thread that was viewed over 13 million times. Emanuel's own X post got nearly half a million views. He also quickly gained about 13,000 followers on the platform, going from about 2,000 to more than 15,000 followers...
[Emanuel] pointed to the fact that so many people in San Jose were reading his blog post. He theorized that many of them were Nvidia employees with thousands — or even millions — of dollars worth of Nvidia stock tied up in employee stock options. With that much money in a single asset, Emanuel speculated that many were already debating whether to hold the stock or sell it to lock in profits. He believes his blog post helped convince some of them to sell. "A lot of the sell pressure you saw on Monday morning wasn't necessarily what you might think. I believe a fair amount of that was from shares that had never been active because they had been sitting in workplace.schwab.com accounts..."
Emanuel stresses he's "the most bullish on AI," with MarketWatch emphasizing that "while the points Emanuel laid out in his blog post might be bearish for Nvidia, he still thinks they paint a positive future for AI." Nevertheless, Monday NVIDIA's market capitalization dropped $600 billion, which MarketWatch calls "the largest single-day market-cap drop to date for any company."
What countless Wall Street firms and investment analysts had seemingly missed was being pointed out by some guy in his apartment.... Matt Levine, the prominent Bloomberg News financial columnist, noted the online chatter that claimed Emanuel's post "was an important catalyst" for the stock-market selloff and said it was a "candidate for the most impactful short research report ever." Emanuel spent the rest of the week booked solid as hedge funds paid him $1,000 per hour to speak on the phone and give his take on Nvidia and AI...
Emanuel wrote that the industry may be running low on quality data to train that AI — that is, a potential "data wall" is looming that could slow down AI scaling and reduce some of that need for training resources... Some of these companies, like Alphabet, have also been investing in building out their own semiconductor chips. For a while, Nvidia's hardware has been the best for training AI, but that might not be the case forever as more companies, such as Cerebras, build better hardware. And other GPU makers like AMD are updating their drivers software to be more competitive with Nvidia... Add all these things together — unsustainable spending and data-center building, less training data to work with, better competing hardware and more efficient AI — and you get a future where it's harder to imagine Nvidia's customers spending as much as they currently are on Nvidia hardware... "If you know that a company will only earn supersized returns for a couple years, you don't apply a multiple. You certainly don't put a 30-times multiple," Emanuel told MarketWatch.
The article notes that DeepSeek "is open-source and has been publishing technical papers out in the open for the past few months... The $5.6 million training-cost statistic that many investors cited for sparking the DeepSeek market panic was actually revealed in the V3 technical paper published on Dec. 26."
Read more of this story at Slashdot.
