It is well known that Warren Buffett's statements can sway market directions, a phenomenon known as the "Buffett Effect." Now, as Michael Burry, the investor famous for predicting the U.S. housing bubble burst, begins disclosing his trades in near real-time, Wall Street is discussing the existence of a so-called "Burry Effect." Although the investor himself does not agree with this label, market performance suggests he may have underestimated his influence.
Burry currently has a large number of subscribers and followers on multiple financial content platforms, and his public trading actions quickly come into market view. This phenomenon seemed to manifest this week. He posted on the platform that he had shorted Micron Technology, having previously disclosed new bearish bets targeting Nvidia, Applied Materials, Caterpillar, Tesla, and exchange-traded funds tracking semiconductor stock indices. He pointed out that some chip equipment stocks are overvalued, believing that the large-scale investment plans announced by Samsung Electronics and SK Hynix mark the beginning of the industry's endgame.
Following the disclosure of these bearish views, related AI hardware and semiconductor stocks quickly encountered sell-offs. In the Korean market, Samsung Electronics and SK Hynix cumulative declines were significant in a short period, reaching 14% and 17% respectively. In the U.S. market, the semiconductor index ETF fell 12% within two trading days, Applied Materials plunged 17%, Micron Technology dropped 15%, and Nvidia retreated nearly 3%. Other stocks on the short list also came under pressure; Caterpillar fell 11% in two days, and despite Tesla announcing a significant increase in Q2 vehicle deliveries, its stock price still fell 6%. Caterpillar's decline attracted particular attention. As AI data center construction boosted demand for power generation equipment, the stock has risen about 68% this year. This short position is seen as a signal of bearishness on the AI capital expenditure chain.
A chief investment strategist stated that a short-term effect indeed exists. Investors know he has a record of identifying excessive prosperity, even if the timing is often early. When he targets market sectors with high valuations, it may trigger investors to sell and lock in profits. This is almost a mirror image of the Buffett Effect; Buffett's investments inspire confidence and attract buying, while short disclosure may encourage investors to take profits and reduce risk. However, some views suggest that related comments often amplify existing market anxiety rather than creating concerns out of thin air. Shorting Caterpillar was an unexpected move that will certainly have an impact, possibly amplifying investor concerns about the stock's overvaluation, becoming part of the narrative against the sustainability of high-growth stock earnings stories.
From Palantir to Micron, this investor continues to target AI trades. After disclosing a short position on Palantir last year, he faced strong backlash from the company's management. He subsequently stated he had directly shorted the stock and recently posted that he had cut his position by half. An investment director noted that he endured considerable criticism for shorting previously, but the stock price of this AI and data analysis software company has now fallen nearly 40% from earlier highs. The short bet indicates an expectation that AI investment will slow as returns disappoint, leading to excess inventory and increased idle capacity. This will impact the entire supply chain, from servers and chips to cooling systems and engineering machinery. History shows he is not afraid to enter early and bear pressure, but short-term speculative capital and passive fund flows may test his judgment.
It remains difficult to judge whether he will ultimately be proven right, but it is certain that public disclosure has become an important sentiment variable in AI trades. Over the past two years, the AI narrative drove significant gains in chips, memory, power equipment, data center infrastructure, and some software stocks. However, as valuations rise, capital expenditures expand, and the market begins to question the speed of return realization, investor tolerance for AI trades is declining. In this context, bearish comments may not be the sole reason for the sell-off but could become a catalyst triggering profit-taking. If the bet succeeds, this effect may strengthen further. For Wall Street, this means AI trades are no longer just about earnings and tech giant capital expenditures; investors must also watch whether a contrarian figure is publicly betting on a bubble burst.
