Here’s a question that should matter to every investor in Palantir Technologies (NASDAQ: PLTR): Of all the S&P 500 companies that have ever traded at a valuation close to Palantir’s, how many actually made investors money?
The answer: extremely few.
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The data analytics and artificial intelligence (AI) company is currently trading around $155 a share and has a market capitalization of $370 billion. The company brought in $4.5 billion in revenue last year, which means shares carry a price-to-sales ratio (P/S) of 87. That makes it the most expensive stock in the S&P 500.
And not just today. Few companies that have ever been included in the index have carried a P/S like that. In fact, according to financial research firm WisdomTree, only 231 have ever reached a P/S of 25. The only S&P 500 companies to reach a P/S of 100 — and Palantir has — came during the irrational exuberance of the dot-com bubble.
The WisdomTree report also said that, of the 231 companies that have reached 25 times sales, just 21% outperformed the market over the following year. Not crush it — just beat it. The median relative return was a huge loss of 36%. And that gets worse the further you extend the time frame. Over three years, 9% came out ahead. Over 20 years, just 4%.
And if you make the club more exclusive, things look even more bleak. Just 148 companies reached a P/S of 40. And only a few of them outperformed the market over the long haul: 3% over 20 years.
And the truth is that many of the companies that lost at these valuations weren’t bad businesses. A lot of them were growing revenue and earnings rapidly. They just couldn’t live up to the expectations investors had placed on them. The bar for a company with a P/S of 40 is incredibly high. The bar for a P/S above 80 is in the stratosphere.
Yet Palantir is clearing that bar right now, and that is genuinely impressive. I am not arguing this point at all. The company is executing at a level that very few can match. The question is: For how long?
I think that, as well as its executing, it could face some real issues scaling up in the not-so-distant future. For as much as it has differentiated itself, I’m not convinced it can continue to remain “one of a kind” while the Microsofts of the world pour billions into enterprise AI.




