Investors turn to AI chip supply chain stocks as profit-seeking overheats

Fonte Cryptopolitan

Investors hunting for ways to profit from artificial intelligence (AI) have typically gravitated toward semiconductor companies. Now they’re discovering businesses that build the machines used to manufacture those chips.

Teradyne Inc. supplies testing tools that check chips during production. The company’s shares have roughly doubled since hitting a low in April and climbed over 40% from late July.

Two other major American firms in this space, Lam Research Corp. and KLA Corp., have posted gains topping 68% this year. That makes them the fourth and sixth strongest performers among the 30 stocks in the Philadelphia Stock Exchange Semiconductor Index.

Lam Research put together an impressive run earlier this month, with shares rising for 14 straight sessions. That winning streak was the longest in company history and pushed the stock up 36%. Applied Materials Inc. followed with its own eight-day rally that delivered a 20% bump.

Tech giants, including Microsoft Corp. and Alphabet Inc., keep pumping money into artificial intelligence projects. Meanwhile, plenty of chipmakers now look pricey. That combination has pushed money toward equipment makers, where investors think they can still find bargains. Those bargains aren’t quite as cheap anymore, though, as more people catch on.

Haris Khurshid runs investments at Karobaar Capital. He thinks the market is betting heavily that factories and cloud companies will keep spending big money.

“The catch is valuations have already run hard, so any pause in orders or delayed spend could hit fast,” Khurshid said as quoted in a Bloomberg’s report.

Memory chips drive demand

Similar patterns are showing up in memory and storage hardware, a corner of tech that doesn’t usually grab headlines. As previously reported by Cryptopolitan, Micron Technology Inc. has jumped over 90% this year thanks to strong demand for high-bandwidth memory that powers artificial intelligence systems.

Lam Research and KLA both supply equipment to Micron. Samsung Electronics Co. and SK Hynix Inc. compete with Micron on memory products, and they happen to be Teradyne’s biggest buyers.

Susquehanna analyst Mehdi Hosseini bumped up his target price for Teradyne last week, going from $133 to $200. His reasoning centered on expectations that memory companies will spend heavily on testing gear. Teradyne closed Monday at $134.33, which means Hosseini sees room for another 49% climb.

Hosseini pointed to Teradyne expanding into different testing areas, including wafer sorting. Taiwan Semiconductor Manufacturing Co. is expected to join that customer list. He told clients in a September 22 note that this growth “is not entirely reflected in the current share price.”

But there’s a problem developing. Even these secondary plays on artificial intelligence are getting expensive, which creates danger if spending slows down. KeyBanc Capital Markets analysts recently downgraded Lam Research, writing that the rally hasn’t been matched by better earnings forecasts or actual results. Morgan Stanley and CFRA both cut their ratings on KLA Corp. last week.

Valuation concerns are mounting

Early in the year, Lam Research and KLA traded around 20 times their forecast profits for the coming 12 months. Now they’re closing in on 30 times. That’s still under Broadcom’s 36 times multiple, but it’s higher than the Philadelphia semiconductor index average. Teradyne sits at 32 times projected earnings, which actually puts it above Nvidia Corp.

Adam Rich helps manage over $17 billion at Vaughan Nelson, where he serves as deputy chief investment officer and portfolio manager. He’s skeptical about how long this can last.

“The rally looks to be on shaky footing, since it seems like exponential investment in AI is the only way for it to keep up, and that seems unlikely,” Rich said. “Right now everyone is winning, and if you’re part of the AI trade, that’s great, but no one wins forever.”

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Isenção de responsabilidade: Apenas para fins informativos. O desempenho passado não é indicativo de resultados futuros.
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