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Michael Burry’s $4m bet against chip sector is down this much

Michael Burry's $4m bet against chip sector is down this much

This week, renowned investor Michael Burry, made famous by “The Big Short,” shifted his bearish outlook from the broader market to a specific sector. 

Q3 securities filings disclosed that Burry’s Scion Asset Management incurred a significant loss after exiting its bearish stance on the S&P 500 and Nasdaq-100. The filings revealed a strategic move as Scion purchased put options worth $47.4 million against the iShares Semiconductor ETF (SOXX) – one of the biggest semiconductor ETFs.

This shift in focus signifies Burry’s pessimistic stance on the chip sector, encompassing major players like AMD (NASDAQ: AMD), Broadcom (NASDAQ: AVGO), Nvidia (NASDAQ: NVDA), Intel (NASDAQ: INTC), and others. 

However, as Q4 unfolds, Burry’s bearish bet on SOXX has yet to yield the expected results, with the ETF seeing a decent rise.

SOXX up 7.5% since the onset of Q4

The last confirmed date Burry held put options in the SOXX ETF was October 2, the last day of the third quarter, according to Michael Burry Stock Tracker

Since that date, the semiconductor-focused fund rose 7.5%, from $476 to $512, the X account that tracks Burry’s trades noted. 

SOXX ETF’s performance since Burry first held put options. Source: Michael Burry Stock Tracker

“Not a good start, but we’ll be here tracking the performance as it plays out.”

it said.

Given the vital role semiconductor companies are playing in the ongoing artificial intelligence (AI) craze, a strong performance is no surprise.

Nvidia and other chipmakers thrived on this year’s AI boom because generative AI products such as OpenAI’s ChatGPT run on high-end chips known as graphics processing units (GPUs). Nvidia, for instance, controls roughly 80% of the GPU market. 

These chips, especially ones made by Nvidia, are designed to efficiently handle specific math tasks involved in AI computing. Conversely, generic central processing units (CPUs) like the ones made by Intel were designed to handle a broader range of assignments with less efficiency. 

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